Job Summary

We are looking for a skilled AI Automation QA Engineer to design, develop, and maintain automated testing solutions for AI-powered applications, machine learning models, and Generative AI systems. In this role, you will collaborate with AI Engineers, Software Developers, Data Scientists, and DevOps teams to ensure AI applications are reliable, scalable, secure, and production-ready. The ideal candidate has strong experience in automation testing, API validation, CI/CD pipelines, and testing AI-driven products such as LLMs, chatbots, recommendation engines, and intelligent automation platforms.

Key Responsibilities

• Design and implement automated test frameworks for AI and machine learning applications.
• Develop and maintain UI, API, regression, integration, and end-to-end automated test suites.
• Validate AI model outputs for accuracy, consistency, reliability, and performance.
• Test Large Language Models (LLMs), AI copilots, chatbots, and Retrieval-Augmented Generation (RAG) applications.
• Create automated test scripts using Python, Selenium, Playwright, or similar frameworks.
• Automate API testing using REST Assured, Postman, or similar tools.
• Integrate automated testing into CI/CD pipelines using Jenkins, GitHub Actions, or Azure DevOps.
• Monitor AI application performance, identify defects, and collaborate with development teams to resolve issues.
• Validate training datasets, model deployments, and inference pipelines.
• Conduct performance, load, security, and compatibility testing for AI applications.
• Generate detailed test reports, defect documentation, and quality metrics.
• Support continuous improvement of QA processes and automation frameworks.

Required Qualifications

• Bachelor's degree in Computer Science, Software Engineering, Information Technology, or a related field.
• 3–6 years of experience in QA Automation or Software Testing.
• Experience testing AI/ML or Generative AI applications is highly preferred.
• Strong programming skills in Python, Java, or JavaScript.
• Hands-on experience with Selenium, Playwright, Cypress, or similar automation frameworks.
• Experience with REST API testing and API automation.
• Knowledge of software development lifecycle (SDLC) and Agile methodologies.
• Familiarity with machine learning concepts and AI workflows.
• Experience with Git, Docker, Kubernetes, and CI/CD tools.
• Excellent analytical, problem-solving, and communication skills.

Preferred Skills

• Large Language Models (LLMs)
• Prompt Engineering
• LangChain or LangGraph
• Retrieval-Augmented Generation (RAG)
• OpenAI APIs or similar AI platforms
• Vector Databases (Pinecone, FAISS, ChromaDB)
• SQL and NoSQL databases
• Jenkins, GitHub Actions, Azure DevOps
• AWS, Azure, or Google Cloud Platform
• Performance testing tools (JMeter, k6)
• AI model evaluation and Responsible AI principles

Technical Skills

• Python
• Selenium
• Playwright
• PyTest
• REST API Testing
• Postman
• SQL
• Git & GitHub
• Jenkins
• Docker
• Kubernetes
• Azure DevOps
• AWS / Azure / GCP
• LangChain
• OpenAI API
• JMeter
• Machine Learning Fundamentals

Benefits

• Competitive salary with annual performance bonus.
• Medical, dental, and vision insurance.
• Paid vacation, holidays, and parental leave.
• Flexible remote or hybrid work options.
• Professional development and AI certification reimbursement.
• Stock options or equity (company-dependent).
• Career growth opportunities in AI Engineering and Automation.

Job Description

We are seeking an experienced Principal AI QA Engineer to lead the quality strategy for enterprise Artificial Intelligence products, including Large Language Models (LLMs), Generative AI applications, AI agents, Retrieval-Augmented Generation (RAG) systems, and machine learning platforms. As a technical leader, you will define AI testing standards, develop scalable quality frameworks, and ensure AI solutions meet the highest levels of accuracy, reliability, safety, performance, and regulatory compliance.

In this role, you will work closely with AI researchers, machine learning engineers, software developers, product managers, MLOps engineers, and security teams to establish end-to-end quality assurance processes throughout the AI development lifecycle. You will drive automation, benchmark model performance, evaluate AI outputs, and lead initiatives to improve the robustness and trustworthiness of production AI systems.

The ideal candidate has deep expertise in software quality engineering, AI testing methodologies, test automation, cloud-native technologies, and modern Generative AI platforms.

Key Responsibilities

• Define and lead the enterprise AI Quality Assurance strategy across multiple AI products and platforms.
• Design and implement comprehensive testing frameworks for Large Language Models (LLMs), Generative AI applications, AI agents, and machine learning systems.
• Develop automated validation pipelines to evaluate model accuracy, consistency, robustness, fairness, and reliability.
• Lead functional, regression, integration, API, performance, security, and end-to-end testing for AI-powered applications.
• Design evaluation methodologies for prompt engineering, prompt optimization, and LLM response quality.
• Create benchmark datasets and automated scoring frameworks to measure AI model performance.
• Validate Retrieval-Augmented Generation (RAG) pipelines, vector search quality, and knowledge retrieval accuracy.
• Conduct adversarial testing to identify hallucinations, prompt injection vulnerabilities, jailbreak attempts, unsafe outputs, and model weaknesses.
• Monitor production AI systems for model drift, latency, reliability, inference quality, and operational health.
• Establish AI quality metrics, testing standards, governance processes, and release criteria.
• Collaborate with cross-functional engineering teams to resolve quality issues and improve AI system performance.
• Mentor QA engineers and promote best practices in AI quality engineering and test automation.
• Support Responsible AI initiatives by evaluating bias, fairness, explainability, privacy, and compliance requirements.
• Analyze production incidents, perform root cause analysis, and implement preventive quality improvements.
• Drive continuous improvement of AI testing frameworks, automation coverage, and engineering processes.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Software Engineering, Data Science, or a related technical field.
• 8+ years of experience in Software Quality Assurance, Test Automation, or Quality Engineering.
• 4+ years of hands-on experience testing AI, Machine Learning, or Generative AI systems.
• Strong experience with Large Language Models (LLMs), AI agents, and enterprise AI platforms.
• Advanced programming skills in Python and experience developing automated testing frameworks.
• Experience with RESTful API testing, automation tools, and CI/CD pipelines.
• Strong understanding of machine learning concepts, model evaluation, and AI validation techniques.
• Experience working with cloud platforms such as AWS, Azure, or Google Cloud Platform.
• Excellent analytical, problem-solving, leadership, and communication skills.

Preferred Qualifications

• Experience evaluating GPT-based models, Claude, Gemini, Llama, or other foundation models.
• Knowledge of Prompt Engineering and prompt evaluation techniques.
• Experience testing Retrieval-Augmented Generation (RAG) applications.
• Familiarity with vector databases and semantic search technologies.
• Experience with Docker, Kubernetes, and MLOps workflows.
• Knowledge of Responsible AI, AI governance, and model risk management.
• Experience performing AI security testing and adversarial evaluations.

Technical Skills

Programming & Scripting

• Python
• SQL
• Java
• JavaScript
• Bash

AI & Machine Learning

• Large Language Models (LLMs)
• Generative AI
• Retrieval-Augmented Generation (RAG)
• AI Agents
• Prompt Engineering
• Machine Learning
• Model Evaluation
• AI Benchmarking
• Responsible AI
• AI Safety Testing

Testing & Automation

• AI Model Validation
• Functional Testing
• Regression Testing
• Integration Testing
• Performance Testing
• Security Testing
• API Testing
• Test Automation
• End-to-End Testing

Tools & Platforms

• PyTest
• Playwright
• Selenium
• Postman
• JMeter
• Jenkins
• GitHub Actions
• Git
• Docker
• Kubernetes

Cloud Technologies

• AWS
• Microsoft Azure
• Google Cloud Platform (GCP)

Preferred Certifications

• ISTQB Advanced Test Automation Engineer
• AWS Certified Machine Learning – Specialty
• Microsoft Azure AI Engineer Associate
• Google Professional Machine Learning Engineer
• Certified Kubernetes Application Developer (CKAD)

Benefits

• Annual performance bonus and potential equity/stock awards.
• Comprehensive medical, dental, and vision insurance.
• Flexible paid time off and company holidays.
• Remote and hybrid work opportunities.
• Professional development and certification reimbursement.
• Wellness and employee assistance programs.
• Paid parental leave.

Job Summary

We are seeking an experienced Principal Business Analytics Consultant to lead enterprise-wide analytics initiatives and help clients solve complex business challenges through data-driven strategies. In this role, you will partner with executive stakeholders to define business objectives, develop analytics roadmaps, and deliver innovative solutions that improve operational efficiency, customer experience, and financial performance.

As a senior leader, you will oversee large-scale consulting engagements, mentor analytics teams, and drive digital transformation initiatives using advanced analytics, artificial intelligence (AI), machine learning (ML), and modern business intelligence platforms. The ideal candidate combines deep analytical expertise with exceptional business acumen and executive communication skills.

Key Responsibilities

• Lead strategic business analytics and digital transformation engagements for enterprise clients.
• Partner with C-suite executives and business leaders to define analytics strategies aligned with organizational goals.
• Design and implement enterprise analytics frameworks, KPIs, and performance measurement systems.
• Analyze complex business data to identify trends, risks, and opportunities for growth.
• Develop executive dashboards, scorecards, and self-service reporting solutions using Power BI, Tableau, or Looker.
• Build predictive models, forecasting solutions, and scenario analyses to support strategic planning.
• Advise clients on analytics modernization, cloud migration, and AI adoption.
• Collaborate with cross-functional teams including Data Engineering, Data Science, Finance, Marketing, Operations, and IT.
• Oversee data governance, data quality, and business intelligence best practices.
• Present actionable recommendations and business cases to executive leadership and client stakeholders.
• Lead workshops, stakeholder interviews, and requirements-gathering sessions.
• Mentor and coach consultants, analysts, and project teams to foster technical and professional growth.
• Support business development by contributing to proposals, solution designs, and client presentations.
• Stay informed about emerging trends in business analytics, AI, automation, and cloud technologies.

Required Qualifications

• Bachelor's degree in Business Analytics, Data Analytics, Computer Science, Information Systems, Economics, Finance, Statistics, or a related field.
• 10+ years of experience in business analytics, business intelligence, management consulting, or enterprise data strategy.
• Demonstrated experience leading large-scale analytics or digital transformation initiatives.
• Advanced proficiency in SQL and data analysis techniques.
• Expertise with business intelligence platforms such as Power BI, Tableau, or Looker.
• Strong understanding of data modeling, data warehousing, and enterprise reporting.
• Experience with cloud data platforms such as Snowflake, Databricks, Amazon Redshift, Google BigQuery, or Azure Synapse Analytics.
• Knowledge of ETL/ELT processes and modern data integration tools.
• Excellent executive communication, presentation, and stakeholder management skills.
• Proven ability to lead cross-functional teams and influence strategic decision-making.

Preferred Qualifications

• Master's degree (MBA, Business Analytics, Data Science, Information Systems, or a related field).
• Experience with AI, machine learning, and predictive analytics initiatives.
• Familiarity with Python or R for advanced analytics.
• Consulting experience at a global professional services firm or enterprise technology company.
• Professional certifications in cloud platforms, business intelligence, or project management (e.g., Microsoft Power BI, AWS, Azure, Google Cloud, PMP).

Technical Skills

Analytics & Business Intelligence

• Power BI
• Tableau
• Looker
• Microsoft Excel (Advanced)
• DAX
• Power Query (M)

Programming & Query Languages

• SQL
• Python
• R

Cloud & Data Platforms

• Snowflake
• Databricks
• Amazon Redshift
• Google BigQuery
• Azure Synapse Analytics
• AWS
• Microsoft Azure
• Google Cloud Platform (GCP)

Data Engineering & Integration

• dbt
• Azure Data Factory
• Informatica
• Talend
• Apache Spark (preferred)

Consulting & Strategy

• Business Process Improvement
• KPI Design
• Executive Reporting
• Digital Transformation
• Data Governance
• Financial & Operational Analytics
• Predictive Analytics
• Change Management

Soft Skills

• Executive communication
• Strategic thinking
• Leadership and team development
• Client relationship management
• Problem-solving and critical thinking
• Negotiation and influence
• Decision-making
• Business storytelling with data
• Project and stakeholder management
• Collaboration across global teams

Compensation & Benefits

• Annual performance bonus (15–30%)
• Equity/RSUs (where applicable)
• Medical, dental, and vision insurance
• 401(k) retirement plan with employer match
• Flexible remote or hybrid work options
• Generous paid time off and company holidays
• Professional development and certification reimbursement
• Employee wellness and mental health programs
• Leadership development opportunities

Job Summary

We are seeking a highly analytical and detail-oriented Senior Business Intelligence Analyst to join our growing Data & Analytics team. In this role, you will transform complex datasets into actionable business insights that support strategic decision-making across the organization. You will collaborate with cross-functional teams—including Finance, Sales, Marketing, Product, Operations, and Executive Leadership—to design scalable reporting solutions, develop interactive dashboards, and deliver meaningful analytics that drive business performance.

The ideal candidate has strong expertise in SQL, data modeling, business intelligence tools such as Power BI or Tableau, and data visualization best practices. Experience with cloud data platforms, ETL processes, and stakeholder management is highly valued.

Key Responsibilities

• Design, build, and maintain executive dashboards and KPI scorecards using Power BI, Tableau, or similar BI tools.
• Develop complex SQL queries to extract, clean, and analyze large datasets from multiple data sources.
• Analyze business trends, customer behavior, operational performance, and financial metrics to identify opportunities for improvement.
• Partner with stakeholders across departments to gather reporting requirements and translate business needs into scalable BI solutions.
• Develop automated reporting processes that improve efficiency and reduce manual effort.
• Create and maintain data models, semantic layers, and reporting datasets for enterprise-wide analytics.
• Perform data validation and quality assurance to ensure reporting accuracy and consistency.
• Identify trends, anomalies, and actionable insights through exploratory data analysis.
• Build forecasting and performance measurement models to support strategic planning.
• Present analytical findings and recommendations to senior leadership in a clear and concise manner.
• Collaborate with Data Engineering teams to optimize data pipelines and warehouse performance.
• Support self-service analytics initiatives by enabling business users with intuitive reporting solutions.
• Establish and document BI standards, reporting methodologies, and best practices.
• Monitor dashboard performance and implement enhancements based on user feedback.
• Stay current with emerging BI technologies, analytics tools, and industry trends.

Required Qualifications

• Bachelor's degree in Business Analytics, Data Analytics, Computer Science, Information Systems, Statistics, Mathematics, Economics, Finance, or a related field.
• 5–8+ years of experience in Business Intelligence, Data Analytics, or Business Analytics.
• Advanced proficiency in SQL for querying and manipulating large datasets.
• Hands-on experience with Power BI, Tableau, Looker, or similar business intelligence platforms.
• Strong understanding of data modeling concepts, relational databases, and data warehousing.
• Experience working with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform.
• Knowledge of ETL processes and data integration techniques.
• Strong analytical, problem-solving, and critical-thinking skills.
• Excellent communication and presentation skills with the ability to explain technical concepts to non-technical audiences.
• Experience working in Agile or Scrum environments.

Preferred Qualifications

• Master's degree in Business Analytics, Data Science, Information Systems, or a related field.
• Experience with Python or R for data analysis and automation.
• Knowledge of data governance and master data management practices.
• Experience with Snowflake, Databricks, Redshift, BigQuery, or Azure Synapse.
• Familiarity with version control tools such as Git.
• Experience building predictive analytics or forecasting models.
• BI platform certifications (e.g., Microsoft Power BI Data Analyst Associate or Tableau Certified Data Analyst).

Technical Skills

Business Intelligence Tools

• Power BI
• Tableau
• Looker
• Qlik Sense
• SAP BusinessObjects

Programming & Query Languages

• SQL
• Python
• R
• DAX
• Power Query (M)

Databases & Data Warehousing

• SQL Server
• PostgreSQL
• MySQL
• Oracle
• Snowflake
• Amazon Redshift
• Google BigQuery
• Azure Synapse Analytics

Cloud Platforms

• AWS
• Microsoft Azure
• Google Cloud Platform (GCP)

Data Integration & ETL

• SQL Server Integration Services (SSIS)
• Azure Data Factory
• Informatica
• Talend
• dbt

Analytics & Reporting

• KPI Development
• Data Visualization
• Forecasting
• Trend Analysis
• Financial Reporting
• Customer Analytics
• Operational Analytics

Collaboration Tools

• Jira
• Confluence
• Microsoft Teams
• Slack

Soft Skills

• Analytical thinking
• Strategic problem-solving
• Stakeholder management
• Business acumen
• Effective communication
• Data storytelling
• Leadership and mentoring
• Collaboration
• Time management
• Attention to detail
• Adaptability
• Decision-making

Career Progression

• Business Intelligence Analyst
• Senior Business Intelligence Analyst
• Lead Business Intelligence Analyst
• Business Intelligence Manager
• Analytics Manager
• Director of Business Intelligence
• Director of Analytics
• Head of Business Intelligence
• Vice President of Analytics
• Chief Data & Analytics Officer (CDAO)

Why Join Us

• Competitive salary and performance-based bonuses.
• Comprehensive medical, dental, and vision insurance.
• Flexible remote or hybrid work options.
• Paid time off, company holidays, and wellness programs.
• Professional development and certification reimbursement.
• Access to cutting-edge analytics tools and cloud technologies.
• Collaborative, data-driven culture with opportunities for career growth.
• Opportunity to influence strategic business decisions through data and analytics.

Job Summary

We are seeking an experienced AI Ethics Specialist to help ensure that our Artificial Intelligence systems are developed and deployed responsibly, ethically, and in compliance with global regulations. In this role, you will collaborate with AI engineers, data scientists, legal teams, product managers, and cybersecurity professionals to identify ethical risks, establish governance frameworks, and promote fairness, transparency, accountability, and privacy across AI initiatives.

The ideal candidate has experience in Responsible AI, AI governance, risk management, algorithmic fairness, and emerging AI regulations, with a strong understanding of machine learning and Generative AI technologies.

Key Responsibilities

• Develop and implement Responsible AI policies, standards, and governance frameworks.
• Evaluate AI systems for fairness, transparency, explainability, bias, and accountability.
• Conduct AI ethics impact assessments and risk analyses for machine learning and Generative AI projects.
• Collaborate with AI development teams to integrate ethical principles throughout the AI lifecycle.
• Monitor compliance with global AI regulations and industry standards.
• Identify and mitigate algorithmic bias, discrimination, and unintended AI outcomes.
• Develop AI governance documentation, ethical guidelines, and best practices.
• Support internal AI ethics review boards and governance committees.
• Work with legal, privacy, compliance, and cybersecurity teams to address AI-related risks.
• Educate employees on Responsible AI principles through workshops and training sessions.
• Stay informed about emerging AI technologies, regulatory developments, and ethical challenges.
• Prepare reports and recommendations for executive leadership regarding AI governance and compliance.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Information Systems, Law, Ethics, Public Policy, or a related field.
• 4–8+ years of experience in AI Governance, Responsible AI, AI Risk Management, Data Ethics, or Technology Compliance.
• Understanding of machine learning, Generative AI, and Large Language Models (LLMs).
• Knowledge of AI fairness, explainability, accountability, transparency, and privacy principles.
• Familiarity with AI governance frameworks and international standards.
• Strong analytical, problem-solving, communication, and stakeholder management skills.
• Experience working with cross-functional technical and business teams.

Preferred Qualifications

• Experience implementing Responsible AI programs in enterprise environments.
• Knowledge of AI risk management frameworks such as the NIST AI Risk Management Framework (AI RMF).
• Familiarity with ISO/IEC 42001, ISO/IEC 23894, and other AI governance standards.
• Experience conducting AI model audits and algorithmic impact assessments.
• Understanding of data privacy regulations, including GDPR, CCPA, and HIPAA.
• Experience with AI model documentation, model cards, and governance reporting.
• Background in cybersecurity governance or enterprise risk management is a plus.

Technical Skills

AI & Machine Learning

• Machine Learning Fundamentals
• Generative AI
• Large Language Models (LLMs)
• Explainable AI (XAI)
• AI Model Evaluation
• Responsible AI Principles

Governance & Compliance

• NIST AI Risk Management Framework (AI RMF)
• ISO/IEC 42001 (AI Management Systems)
• ISO/IEC 23894 (AI Risk Management)
• GDPR
• CCPA
• HIPAA
• SOC 2
• ISO 27001

Programming & Data

• Python (preferred)
• SQL
• Jupyter Notebook
• Git
• Data Analysis

AI Platforms & Tools

• OpenAI API
• Azure AI
• AWS AI Services
• Google Vertex AI
• Hugging Face
• IBM watsonx

Preferred Certifications

• Microsoft Certified: Azure AI Engineer Associate (AI-102)
• Certified Information Systems Security Professional (CISSP)
• Certified Information Privacy Professional (CIPP)
• ISO/IEC 42001 Lead Implementer
• ISO/IEC 27001 Lead Implementer
• NIST AI Risk Management Framework Training
• Google Professional Machine Learning Engineer (Preferred)

Benefits

• Competitive salary with annual performance bonuses
• Medical, dental, and vision insurance
• Paid vacation, holidays, and parental leave
• Flexible hybrid work environment
• Professional development and certification reimbursement
• Access to enterprise AI research and innovation programs
• Career growth opportunities in AI Governance, Responsible AI, and AI Strategy

Job Summary

We are seeking an experienced Applied AI & Machine Learning Scientist to develop and deploy cutting-edge artificial intelligence and machine learning solutions that solve complex business and engineering challenges. In this role, you will research, build, and optimize predictive models, deep learning systems, and Generative AI applications while collaborating with software engineers, data scientists, and product teams. The ideal candidate is passionate about AI innovation and has hands-on experience delivering production-ready machine learning solutions at scale.

Key Responsibilities

• Design, develop, and deploy machine learning and deep learning models for production environments.
• Build AI-powered applications using supervised, unsupervised, and reinforcement learning techniques.
• Develop and optimize Large Language Model (LLM) and Generative AI solutions.
• Perform data preprocessing, feature engineering, and exploratory data analysis.
• Train, evaluate, and fine-tune machine learning models to improve performance and accuracy.
• Collaborate with Data Engineers and MLOps teams to build scalable AI pipelines.
• Deploy AI models using cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP).
• Monitor model performance and implement continuous improvements.
• Conduct research on emerging AI technologies and evaluate their business applications.
• Develop recommendation systems, predictive analytics, computer vision, or natural language processing (NLP) solutions.
• Document AI models, experiments, and technical processes.
• Follow Responsible AI, data privacy, and model governance best practices.

Required Qualifications

• Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Statistics, or a related field (Bachelor's degree with equivalent industry experience may also be considered).
• 4–8+ years of experience in Machine Learning, Artificial Intelligence, or Data Science.
• Strong programming skills in Python and SQL.
• Experience with machine learning frameworks such as TensorFlow, PyTorch, Scikit-learn, or XGBoost.
• Strong understanding of statistics, probability, optimization, and predictive modeling.
• Experience deploying machine learning models into production environments.
• Familiarity with cloud platforms including AWS, Microsoft Azure, or Google Cloud Platform (GCP).
• Excellent analytical, problem-solving, and communication skills.

Preferred Qualifications

• Experience with Large Language Models (LLMs) and Generative AI technologies.
• Hands-on experience with Retrieval-Augmented Generation (RAG), vector databases, and prompt engineering.
• Experience with NLP, computer vision, recommendation systems, or time-series forecasting.
• Knowledge of MLOps tools such as MLflow, Kubeflow, SageMaker, or Vertex AI.
• Experience with distributed computing frameworks such as Apache Spark or Ray.
• Publications or contributions to AI research or open-source machine learning projects are a plus.

Technical Skills

• Programming: Python, SQL, R
• Machine Learning: Scikit-learn, XGBoost, LightGBM
• Deep Learning: TensorFlow, PyTorch, Keras
• Generative AI: OpenAI API, Hugging Face Transformers, LangChain, LlamaIndex
• Large Language Models: GPT, Llama, Mistral, Gemini
• Data Processing: Pandas, NumPy, Apache Spark
• Cloud Platforms: AWS, Microsoft Azure, Google Cloud Platform (GCP)
• MLOps: MLflow, Kubeflow, Docker, Kubernetes
• Visualization: Tableau, Power BI, Matplotlib
• Version Control: Git, GitHub

Preferred Certifications

• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure AI Engineer Associate (AI-102)
• Google Professional Machine Learning Engineer
• Databricks Certified Machine Learning Professional
• TensorFlow Developer Certificate

Benefits

• Competitive salary with annual performance bonuses
• Medical, dental, and vision insurance
• Paid vacation, holidays, and parental leave
• Hybrid work flexibility
• Learning and certification reimbursement
• Access to advanced AI research and high-performance computing resources
• Career growth opportunities in AI, machine learning, and data science

Job Summary

We are seeking a highly skilled Cloud Security Engineer to join our cybersecurity team. In this role, you will design, implement, and maintain security controls across cloud platforms including AWS, Microsoft Azure, and Google Cloud Platform (GCP). You will work closely with DevOps, Infrastructure, and Security Operations teams to protect cloud environments, ensure regulatory compliance, and respond to security incidents. The ideal candidate has strong expertise in cloud architecture, identity and access management (IAM), network security, and automation.

Key Responsibilities

• Design, implement, and manage secure cloud infrastructure across AWS, Azure, and GCP.
• Develop and enforce cloud security policies, standards, and best practices.
• Configure and maintain Identity and Access Management (IAM), Multi-Factor Authentication (MFA), and Role-Based Access Control (RBAC).
• Implement Zero Trust security architecture and cloud-native security controls.
• Monitor cloud environments using SIEM, CSPM, and cloud security monitoring tools.
• Perform cloud vulnerability assessments, risk analyses, and security audits.
• Secure Kubernetes clusters, containers, and serverless applications.
• Automate cloud security tasks using Infrastructure as Code (Terraform, CloudFormation, ARM/Bicep).
• Configure Web Application Firewalls (WAF), firewalls, VPNs, and network segmentation.
• Collaborate with DevOps teams to integrate security into CI/CD pipelines (DevSecOps).
• Investigate and respond to cloud security incidents, threats, and vulnerabilities.
• Ensure compliance with industry standards such as ISO 27001, SOC 2, HIPAA, PCI-DSS, and NIST.
• Maintain cloud security documentation, policies, and incident reports.
• Stay up to date with emerging cloud threats, technologies, and security trends.

Required Qualifications

• Bachelor's degree in Cybersecurity, Information Technology, Computer Science, or a related field (or equivalent experience).
• 3–7+ years of experience in cloud security or cybersecurity.
• Hands-on experience with AWS, Microsoft Azure, or Google Cloud Platform (GCP).
• Strong understanding of cloud networking, IAM, encryption, and security architecture.
• Experience with SIEM, CSPM, and cloud monitoring solutions.
• Knowledge of Infrastructure as Code (Terraform, CloudFormation, ARM/Bicep).
• Experience securing Kubernetes, Docker, and containerized workloads.
• Familiarity with scripting languages such as Python, PowerShell, or Bash.
• Knowledge of security frameworks including NIST, CIS Benchmarks, ISO 27001, and SOC 2.
• Excellent analytical, troubleshooting, and communication skills.

Preferred Qualifications

• Cloud security certifications such as AWS Certified Security – Specialty, Microsoft Azure Security Engineer (AZ-500), or Google Professional Cloud Security Engineer.
• Experience with Microsoft Defender for Cloud, Prisma Cloud, Wiz, Orca Security, or Lacework.
• Knowledge of CI/CD security and DevSecOps practices.
• Experience with threat detection, incident response, and digital forensics.
• Familiarity with compliance frameworks including FedRAMP and PCI-DSS.

Technical Skills

• Cloud Platforms: AWS, Microsoft Azure, Google Cloud Platform (GCP)
• Identity & Access: IAM, Azure AD, Entra ID, MFA, RBAC
• Cloud Security: CSPM, CWPP, WAF, Zero Trust, Cloud Firewall
• Containers: Docker, Kubernetes, Amazon EKS, Azure AKS, Google GKE
• Infrastructure as Code: Terraform, CloudFormation, ARM, Bicep
• Programming: Python, PowerShell, Bash
• Monitoring & SIEM: Microsoft Sentinel, Splunk, Microsoft Defender for Cloud, AWS Security Hub, Azure Monitor
• DevSecOps: GitHub Actions, Jenkins, Azure DevOps, GitLab CI/CD
• Compliance: NIST, ISO 27001, SOC 2, HIPAA, PCI-DSS, CIS Benchmarks

Preferred Certifications

• AWS Certified Security – Specialty
• Microsoft Certified: Azure Security Engineer Associate (AZ-500)
• Google Professional Cloud Security Engineer
• Certified Information Systems Security Professional (CISSP)
• Certified Cloud Security Professional (CCSP)

Benefits

• Competitive salary with annual performance bonus
• Medical, dental, and vision insurance
• Paid time off and company holidays
• Flexible remote/hybrid work options
• Professional certification reimbursement
• Learning and development opportunities
• Career growth within a global cybersecurity team

Job Summary

We are seeking a talented Network Automation Engineer to design, develop, and implement automation solutions that improve the efficiency, scalability, and reliability of enterprise network infrastructure. In this role, you will automate network provisioning, configuration management, monitoring, and operational workflows across on-premises, cloud, and hybrid environments.

You will work closely with Network Engineers, Cloud Engineers, DevOps teams, and Security professionals to build Infrastructure as Code (IaC) solutions, automate repetitive tasks, and modernize network operations using programmable networking technologies. The ideal candidate has strong experience with Python, network automation frameworks, APIs, and enterprise networking technologies.

Key Responsibilities

• Design, develop, and maintain network automation solutions for enterprise infrastructure.
• Automate network configuration, provisioning, deployment, and lifecycle management.
• Develop Python scripts and automation tools to streamline daily network operations.
• Build Infrastructure as Code (IaC) solutions using Ansible, Terraform, and similar automation platforms.
• Integrate network devices with REST APIs, NETCONF, RESTCONF, and other programmable interfaces.
• Automate software upgrades, configuration backups, compliance validation, and change management.
• Develop reusable automation playbooks and workflows for network operations.
• Collaborate with Network, Cloud, DevOps, and Security teams to improve infrastructure efficiency.
• Troubleshoot network automation scripts, APIs, and deployment issues.
• Monitor automation processes and optimize performance, reliability, and scalability.
• Maintain network documentation, automation libraries, and technical standards.
• Support enterprise routing, switching, wireless, firewall, and cloud networking environments.
• Participate in disaster recovery planning and business continuity initiatives.
• Stay current with emerging networking technologies, automation frameworks, and industry best practices.

Required Qualifications

• Bachelor's degree in Computer Science, Information Technology, Network Engineering, or a related field.
• 3–6+ years of experience in enterprise networking, network engineering, or network automation.
• Strong knowledge of routing and switching technologies.
• Experience with Python scripting for network automation.
• Hands-on experience with Ansible, Terraform, or similar Infrastructure as Code tools.
• Experience using REST APIs and network programmability technologies.
• Strong understanding of TCP/IP networking, VLANs, VPNs, routing protocols, and network security.
• Experience with Linux operating systems and shell scripting.
• Excellent troubleshooting, analytical, and problem-solving skills.
• Strong communication and collaboration abilities.

Preferred Qualifications

• Experience with Cisco DNA Center, Cisco ACI, Juniper Apstra, or Arista CloudVision.
• Experience working in cloud networking environments (AWS, Microsoft Azure, or Google Cloud Platform).
• Familiarity with DevOps methodologies and CI/CD pipelines.
• Experience with Software-Defined Networking (SDN) and SD-WAN technologies.
• Knowledge of network monitoring and observability platforms.
• Experience with containerized networking and Kubernetes.
• Familiarity with Zero Trust networking and network security automation.

Technical Skills

Programming & Automation

• Python
• Bash
• PowerShell
• Ansible
• Terraform
• Git
• YAML
• JSON

Networking Technologies

• TCP/IP
• LAN/WAN
• VLAN
• VPN
• MPLS
• SD-WAN
• DNS
• DHCP
• NAT
• QoS

Routing & Switching

• Cisco IOS
• Cisco NX-OS
• Juniper Junos
• Arista EOS
• BGP
• OSPF
• EIGRP
• STP

Network Programmability

• REST APIs
• NETCONF
• RESTCONF
• gNMI
• YANG Models
• Cisco DNA Center API
• Cisco Meraki API

Cloud Networking

• AWS VPC
• Microsoft Azure Virtual Network
• Google Cloud VPC
• Hybrid Cloud Networking
• VPN Gateway
• Direct Connect
• ExpressRoute

Monitoring & Observability

• SolarWinds
• Grafana
• Prometheus
• Splunk
• Wireshark
• Nagios
• ThousandEyes

Operating Systems

• Linux
• Windows Server

Version Control & DevOps

• Git
• GitHub
• GitLab
• Jenkins
• CI/CD Pipelines

Preferred Certifications

• Cisco Certified Network Professional (CCNP Enterprise)
• Cisco Certified DevNet Professional
• Cisco Certified DevNet Associate
• Juniper Networks Certified Professional (JNCIP)
• AWS Certified Advanced Networking – Specialty
• HashiCorp Terraform Associate
• Red Hat Certified System Administrator (RHCSA)
• Microsoft Certified: Azure Network Engineer Associate

Soft Skills

• Strong analytical and problem-solving abilities
• Excellent verbal and written communication skills
• Ability to work in cross-functional teams
• Project planning and time management
• Attention to detail and documentation
• Adaptability in fast-paced environments
• Continuous learning mindset
• Customer-focused approach

Benefits

• Competitive salary with annual performance bonus
• Medical, dental, and vision insurance
• Flexible remote and hybrid work options
• Paid vacation, holidays, and sick leave
• Paid parental leave
• Professional certification reimbursement
• Learning and development budget
• Employee stock purchase plan or equity (where applicable)
• Wellness and employee assistance programs
• Career growth and leadership development opportunities

Job Summary

We are seeking an experienced Senior Data Scientist to join our growing Data Science and Artificial Intelligence team. In this role, you will leverage advanced analytics, statistical modeling, and machine learning to solve complex business problems and drive strategic decision-making. You will work with large-scale structured and unstructured datasets to build predictive models, develop AI-powered solutions, and deliver actionable insights that support business growth.

As a Senior Data Scientist, you will collaborate closely with data engineers, software developers, product managers, business stakeholders, and executive leadership to transform data into innovative products and measurable business value. The ideal candidate has strong technical expertise in machine learning, statistical analysis, programming, cloud platforms, and data visualization, along with excellent communication and leadership skills.

Key Responsibilities

• Design, develop, and deploy predictive, statistical, and machine learning models to solve business challenges.
• Analyze large, complex datasets to identify trends, patterns, and actionable insights.
• Build forecasting, recommendation, classification, clustering, and optimization models.
• Perform exploratory data analysis (EDA), feature engineering, and data preprocessing.
• Develop scalable data science solutions that support production applications.
• Evaluate and improve machine learning model performance using appropriate metrics and validation techniques.
• Partner with Data Engineering teams to develop reliable data pipelines and ensure data quality.
• Collaborate with Product Managers, Software Engineers, and business stakeholders to understand business requirements and translate them into analytical solutions.
• Present findings and recommendations to technical and non-technical audiences, including executive leadership.
• Build dashboards, reports, and visualizations that communicate business insights effectively.
• Implement model monitoring processes to detect model drift and maintain production performance.
• Support A/B testing, experimentation, and causal inference analyses to optimize products and business strategies.
• Mentor junior Data Scientists and contribute to technical best practices across the team.
• Stay current with emerging technologies, AI trends, machine learning techniques, and industry best practices.
• Maintain documentation for models, experiments, methodologies, and technical solutions.

Required Qualifications

• Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, Artificial Intelligence, Engineering, or a related field.
• 4–8+ years of professional experience in Data Science, Machine Learning, or Advanced Analytics.
• Strong expertise in statistical analysis, predictive modeling, and machine learning algorithms.
• Experience working with large-scale datasets and distributed computing frameworks.
• Proficiency in Python and SQL for data analysis and model development.
• Experience deploying machine learning models into production environments.
• Strong understanding of cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform.
• Excellent problem-solving, analytical thinking, and communication skills.
• Ability to work independently and collaboratively in cross-functional teams.

Preferred Qualifications

• Master's degree or Ph.D. in Data Science, Artificial Intelligence, Statistics, Computer Science, or a related field.
• Experience with Generative AI, Large Language Models (LLMs), or Retrieval-Augmented Generation (RAG).
• Experience with MLOps and machine learning deployment pipelines.
• Knowledge of data governance, responsible AI, and model explainability.
• Experience working in Agile software development environments.
• Prior experience mentoring technical team members or leading data science initiatives.

Technical Skills

Programming Languages

• Python
• SQL
• R (Preferred)
• Scala (Preferred)

Machine Learning & AI

• Supervised Learning
• Unsupervised Learning
• Deep Learning
• Reinforcement Learning
• Natural Language Processing (NLP)
• Computer Vision
• Time Series Forecasting
• Recommendation Systems
• Generative AI
• Large Language Models (LLMs)

Data Science Libraries

• Scikit-learn
• TensorFlow
• PyTorch
• XGBoost
• LightGBM
• Pandas
• NumPy
• SciPy

Data Visualization

• Tableau
• Microsoft Power BI
• Matplotlib
• Plotly

Big Data Technologies

• Apache Spark
• Hadoop
• Databricks
• Snowflake

Cloud Platforms

• Amazon Web Services (AWS)
• Microsoft Azure
• Google Cloud Platform (GCP)

Databases

• PostgreSQL
• MySQL
• SQL Server
• MongoDB

Tools

• Git
• Docker
• Kubernetes
• MLflow
• Airflow
• Jupyter Notebook

Preferred Certifications

• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure Data Scientist Associate
• Google Professional Machine Learning Engineer
• Databricks Certified Machine Learning Professional
• TensorFlow Developer Certificate
• SAS Certified Data Scientist

Soft Skills

• Strong analytical and critical thinking abilities
• Excellent verbal and written communication
• Leadership and mentoring capabilities
• Business problem-solving mindset
• Collaboration across cross-functional teams
• Time management and project prioritization
• Adaptability in fast-paced environments
• Strong presentation and stakeholder management skills

Benefits

• Competitive salary with annual performance bonus
• Comprehensive medical, dental, and vision insurance
• Flexible remote and hybrid work options
• Paid vacation, holidays, and sick leave
• Paid parental leave
• Employee stock purchase plan or equity (where applicable)
• Learning and development budget
• Certification reimbursement
• Wellness and mental health programs
• Career advancement opportunities
• Collaborative and inclusive work environment

Job Description

We are seeking an innovative AI Security Engineer to safeguard our artificial intelligence and machine learning platforms from evolving cyber threats. In this role, you will design and implement security controls for AI systems, large language models (LLMs), machine learning pipelines, and cloud-native AI applications. You will work closely with AI researchers, software engineers, cloud architects, and security teams to ensure AI solutions are secure, compliant, resilient, and trustworthy throughout the development lifecycle.

The ideal candidate has strong expertise in cybersecurity, cloud security, AI/ML technologies, secure software development, and modern security frameworks. Experience securing generative AI applications, mitigating prompt injection attacks, protecting training data, and implementing AI governance is highly desirable.

Key Responsibilities

• Design, implement, and maintain security architectures for AI and machine learning systems.
• Secure Large Language Model (LLM) applications against prompt injection, jailbreak attempts, model manipulation, and data leakage.
• Perform security assessments, penetration testing, and threat modeling for AI applications and APIs.
• Protect machine learning pipelines from adversarial attacks, model poisoning, model inversion, and data poisoning.
• Build automated security controls for MLOps and AI deployment pipelines.
• Collaborate with development teams to integrate security into AI application development using DevSecOps best practices.
• Implement Identity and Access Management (IAM) controls for AI platforms and cloud environments.
• Monitor AI infrastructure for suspicious activity, vulnerabilities, and security incidents.
• Develop detection rules and incident response playbooks for AI-specific cyber threats.
• Conduct AI risk assessments and recommend mitigation strategies.
• Ensure compliance with industry standards, privacy regulations, and AI governance policies.
• Research emerging AI threats and recommend proactive security improvements.
• Perform security code reviews and vulnerability assessments for AI-powered applications.
• Work with cloud teams to secure AI workloads deployed on AWS, Azure, or Google Cloud.
• Create technical documentation, security reports, and security awareness materials for AI development teams.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Cybersecurity, Artificial Intelligence, Information Technology, or a related field.
• 3–7+ years of experience in cybersecurity, cloud security, application security, or AI security.
• Experience with AI/ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Strong understanding of cybersecurity principles, secure coding practices, and threat modeling.
• Experience securing cloud environments (AWS, Azure, or Google Cloud Platform).
• Knowledge of MLOps pipelines and CI/CD security.
• Familiarity with AI governance, privacy, and regulatory compliance.
• Strong scripting or programming skills in Python, Java, or Go.
• Excellent analytical, problem-solving, and communication skills.

Preferred Skills

• AI Security
• Large Language Models (LLMs)
• Prompt Injection Defense
• Adversarial Machine Learning
• Machine Learning Security
• MLOps
• DevSecOps
• Cloud Security (AWS, Azure, GCP)
• Kubernetes
• Docker
• Terraform
• Python
• TensorFlow
• PyTorch
• SIEM (Splunk, Microsoft Sentinel)
• MITRE ATT&CK
• Zero Trust Architecture
• Identity & Access Management (IAM)
• API Security
• Threat Intelligence
• Incident Response
• Vulnerability Management
• Secure Software Development Lifecycle (SSDLC)

Preferred Certifications

• Certified Information Systems Security Professional (CISSP)
• GIAC Certified Incident Handler (GCIH)
• GIAC Cloud Security Automation (GCSA)
• AWS Certified Security – Specialty
• Microsoft Certified: Azure Security Engineer Associate
• Certified Cloud Security Professional (CCSP)
• Offensive Security Certified Professional (OSCP) (preferred for offensive AI security testing)

Benefits

• Competitive salary and annual performance bonus
• Comprehensive medical, dental, and vision insurance
• Flexible remote and hybrid work options
• Paid vacation, holidays, and parental leave
• Professional development and certification reimbursement
• Learning budget for AI and cybersecurity training
• Employee stock purchase or equity program (where applicable)
• Wellness and employee assistance programs

Job Description

We are seeking a highly skilled Applied AI Scientist to join our Artificial Intelligence team and develop innovative AI solutions that address complex business and customer challenges. In this role, you will research, design, develop, and deploy advanced machine learning and Generative AI models into production environments. You will work with cross-functional teams to transform cutting-edge AI research into scalable, real-world applications across industries such as finance, healthcare, retail, cybersecurity, manufacturing, and enterprise software.

The ideal candidate has strong expertise in machine learning, deep learning, natural language processing (NLP), computer vision, Large Language Models (LLMs), and cloud-based AI platforms. You will play a key role in building AI-powered products, improving business processes, and driving innovation through data-driven decision-making.

Key Responsibilities

• Design, develop, and deploy advanced machine learning and deep learning models for real-world business applications.
• Build and optimize Generative AI solutions using Large Language Models (LLMs) and foundation models.
• Develop Retrieval-Augmented Generation (RAG) pipelines to enhance AI application accuracy and knowledge retrieval.
• Fine-tune, evaluate, and optimize pre-trained AI models for performance, scalability, and reliability.
• Analyze structured and unstructured datasets to extract actionable insights and support strategic business decisions.
• Collaborate with product managers, software engineers, data scientists, and AI researchers to deliver production-ready AI solutions.
• Implement AI model monitoring, evaluation, and continuous improvement processes.
• Develop feature engineering pipelines, model validation frameworks, and experimentation methodologies.
• Integrate AI models into cloud-native applications and enterprise systems using scalable APIs and MLOps practices.
• Conduct research on emerging AI technologies and recommend innovative solutions.
• Ensure AI systems adhere to responsible AI principles, fairness, explainability, security, and regulatory compliance.
• Document technical designs, research findings, and model performance metrics.
• Mentor junior data scientists and machine learning engineers while promoting AI best practices across teams.

Required Qualifications

• Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Statistics, Mathematics, or a related field.
• 5+ years of experience developing and deploying machine learning or AI solutions.
• Strong expertise in supervised, unsupervised, and deep learning techniques.
• Hands-on experience with Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG).
• Proficiency in Python and experience with TensorFlow, PyTorch, or JAX.
• Strong understanding of statistics, optimization, probability, and linear algebra.
• Experience deploying AI models in cloud environments (AWS, Microsoft Azure, or Google Cloud Platform).
• Excellent problem-solving, analytical, and communication skills.

Preferred Qualifications

• Experience with multimodal AI systems and AI agents.
• Familiarity with reinforcement learning and AI model evaluation.
• Knowledge of MLOps, CI/CD pipelines, and containerized deployments.
• Experience with vector databases and semantic search technologies.
• Published AI research papers or contributions to open-source AI projects.
• Experience working with distributed machine learning systems and GPU-based training.

Technical Skills

Programming Languages

• Python
• SQL
• C++
• Java
• Scala

AI & Machine Learning

• Machine Learning
• Deep Learning
• Generative AI
• Large Language Models (LLMs)
• Natural Language Processing (NLP)
• Computer Vision
• Reinforcement Learning
• Retrieval-Augmented Generation (RAG)
• Prompt Engineering
• AI Agents

Frameworks & Libraries

• TensorFlow
• PyTorch
• JAX
• Hugging Face Transformers
• LangChain
• LlamaIndex
• Scikit-learn
• XGBoost
• MLflow

Cloud & Infrastructure

• AWS
• Microsoft Azure
• Google Cloud Platform (GCP)
• Docker
• Kubernetes
• Databricks
• Apache Spark

Databases & Tools

• Pinecone
• Weaviate
• ChromaDB
• PostgreSQL
• Git
• REST APIs

Preferred Certifications

• AWS Certified Machine Learning – Specialty
• Google Professional Machine Learning Engineer
• Microsoft Certified: Azure AI Engineer Associate
• Databricks Certified Machine Learning Professional
• TensorFlow Developer Certificate

Soft Skills

• Analytical Thinking
• Innovation and Research
• Critical Problem Solving
• Technical Communication
• Cross-Functional Collaboration
• Leadership and Mentoring
• Strategic Thinking
• Continuous Learning
• Business Acumen
• Project Management

Career Growth

• Senior Applied AI Scientist
• Principal AI Scientist
• Staff AI Scientist
• AI Research Scientist
• AI Solutions Architect
• Director of Artificial Intelligence
• Vice President of AI
• Chief AI Officer (CAIO)

Job Description

We are seeking an innovative Machine Learning Research Scientist to join our AI Research team and drive the development of next-generation machine learning technologies. In this role, you will conduct advanced research, design state-of-the-art algorithms, and develop scalable AI models that solve complex real-world problems across domains such as natural language processing (NLP), computer vision, recommendation systems, predictive analytics, and generative AI.

You will collaborate with data scientists, software engineers, research scientists, and product teams to transform cutting-edge research into production-ready AI solutions. The ideal candidate has a strong background in machine learning, deep learning, mathematics, and large-scale data analysis, with a passion for innovation and scientific discovery.

Key Responsibilities

• Conduct advanced research in machine learning, deep learning, and artificial intelligence.
• Design, develop, and evaluate novel machine learning algorithms and models.
• Build and optimize large-scale predictive and generative AI models.
• Research and improve Large Language Models (LLMs), foundation models, and multimodal AI systems.
• Develop scalable AI solutions for NLP, computer vision, recommendation systems, and time-series forecasting.
• Perform statistical analysis, feature engineering, and model experimentation.
• Design and execute research experiments to validate model performance.
• Collaborate with engineering teams to deploy machine learning models into production.
• Publish research papers, technical reports, patents, and conference presentations.
• Stay current with the latest advancements in AI, machine learning, and data science.
• Mentor junior researchers and data scientists.
• Ensure AI models are accurate, reliable, scalable, and ethically developed.

Required Qualifications

• Master's or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, Data Science, Statistics, Mathematics, or a related field.
• 5+ years of experience in machine learning research or applied AI.
• Strong knowledge of supervised, unsupervised, reinforcement, and deep learning techniques.
• Experience with large-scale datasets and distributed machine learning systems.
• Proficiency in Python and ML frameworks such as TensorFlow or PyTorch.
• Strong mathematical foundation in linear algebra, probability, optimization, and statistics.
• Experience publishing research papers or contributing to open-source AI projects is preferred.
• Excellent analytical, problem-solving, and communication skills.

Preferred Qualifications

• Experience with Generative AI and Large Language Models (LLMs).
• Knowledge of reinforcement learning and multimodal AI.
• Experience with cloud platforms (AWS, Azure, or Google Cloud).
• Familiarity with MLOps and model deployment.
• Experience with distributed training and GPU computing.
• Publications in leading AI conferences (NeurIPS, ICML, ICLR, CVPR, ACL, etc.).
• Experience with responsible AI and model governance.

Technical Skills

Programming Languages

• Python
• C++
• Java
• Scala
• SQL

Machine Learning & AI

• Machine Learning
• Deep Learning
• Generative AI
• Large Language Models (LLMs)
• Reinforcement Learning
• Natural Language Processing (NLP)
• Computer Vision
• Recommendation Systems
• Time-Series Forecasting

Frameworks & Libraries

• TensorFlow
• PyTorch
• Scikit-learn
• Hugging Face Transformers
• XGBoost
• LightGBM
• MLflow

Data & Cloud Technologies

• Apache Spark
• Databricks
• Snowflake
• Docker
• Kubernetes
• AWS
• Microsoft Azure
• Google Cloud Platform (GCP)

Data Visualization

• Tableau
• Power BI
• Matplotlib
• Plotly

Preferred Certifications

• AWS Certified Machine Learning – Specialty
• Google Professional Machine Learning Engineer
• Microsoft Certified: Azure AI Engineer Associate
• TensorFlow Developer Certificate
• Databricks Certified Machine Learning Professional

Soft Skills

• Critical Thinking
• Research & Innovation
• Scientific Problem Solving
• Analytical Thinking
• Collaboration
• Technical Writing
• Presentation Skills
• Leadership
• Mentoring
• Continuous Learning

Career Growth

• Senior Machine Learning Research Scientist
• Principal Machine Learning Scientist
• Distinguished AI Scientist
• AI Research Lead
• Director of AI Research
• Head of Machine Learning
• Vice President of AI
• Chief AI Officer (CAIO)

Job Summary

We are seeking an innovative Cybersecurity Research Scientist to join our advanced security research team. In this role, you will conduct cutting-edge research to identify emerging cyber threats, develop next-generation defense techniques, and improve the security of enterprise systems, cloud platforms, artificial intelligence (AI), and critical infrastructure.

You will collaborate with security engineers, data scientists, software developers, and threat intelligence teams to create novel cybersecurity solutions, publish technical research, and translate research findings into practical security technologies. This position is ideal for candidates passionate about solving complex security challenges through scientific research, experimentation, and innovation.

Key Responsibilities

• Conduct advanced research on emerging cyber threats, attack techniques, and security vulnerabilities.
• Design and develop innovative cybersecurity solutions using artificial intelligence, machine learning, and data analytics.
• Perform malware analysis, reverse engineering, and exploit research.
• Research adversarial AI, model security, and AI-driven cyber defense strategies.
• Develop threat detection algorithms and behavioral analytics models.
• Create proof-of-concept security tools, prototypes, and research frameworks.
• Publish technical papers, white papers, patents, and security research reports.
• Collaborate with software engineering teams to integrate research findings into production security solutions.
• Analyze zero-day vulnerabilities and emerging attack vectors.
• Conduct penetration testing research and exploit development for defensive purposes.
• Evaluate new security technologies, frameworks, and industry standards.
• Participate in threat hunting, digital forensics, and incident investigations.
• Present research findings at conferences, internal technical forums, and customer briefings.
• Mentor junior researchers and security engineers.
• Stay current with the latest cybersecurity trends, academic research, and global threat intelligence.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Cybersecurity, Information Security, Software Engineering, or a related field.
• Ph.D. preferred for advanced research positions.
• 5+ years of experience in cybersecurity research, security engineering, or applied security.
• Strong understanding of operating systems, networking, and distributed systems.
• Experience conducting security research and vulnerability analysis.
• Proficiency in Python, C++, Rust, Go, or Java.
• Experience with Linux, Windows, and cloud environments.
• Strong analytical, problem-solving, and research skills.
• Excellent technical writing and presentation abilities.

Preferred Qualifications

• Experience with AI/ML security research.
• Knowledge of cloud security (AWS, Azure, Google Cloud).
• Familiarity with Kubernetes and container security.
• Experience in malware reverse engineering.
• Knowledge of cryptography and secure protocol design.
• Contributions to open-source security projects.
• Published cybersecurity research papers or patents.
• Experience working in research labs or advanced security teams.

Technical Skills

Programming Languages

• Python
• C++
• Go
• Rust
• Java
• Bash
• PowerShell

Cybersecurity

• Threat Intelligence
• Threat Hunting
• Digital Forensics
• Malware Analysis
• Reverse Engineering
• Vulnerability Research
• Incident Response
• Secure Software Development
• Adversarial AI
• Security Automation

Cloud & Infrastructure

• AWS
• Microsoft Azure
• Google Cloud Platform (GCP)
• Docker
• Kubernetes
• Terraform

AI & Data Science

• Machine Learning
• Deep Learning
• TensorFlow
• PyTorch
• Scikit-learn
• Large Language Model (LLM) Security
• AI Model Evaluation

Security Tools

• Splunk
• Microsoft Sentinel
• CrowdStrike Falcon
• Palo Alto Cortex XDR
• Wireshark
• Burp Suite
• Metasploit
• Ghidra
• IDA Pro
• YARA
• Sigma Rules

Preferred Certifications

• CISSP (Certified Information Systems Security Professional)
• GIAC Reverse Engineering Malware (GREM)
• GIAC Certified Incident Handler (GCIH)
• GIAC Certified Forensic Analyst (GCFA)
• Certified Ethical Hacker (CEH)
• Offensive Security Certified Professional (OSCP)
• AWS Certified Security – Specialty
• Microsoft Certified: Cybersecurity Architect Expert

Soft Skills

• Critical Thinking
• Research & Innovation
• Analytical Problem Solving
• Technical Communication
• Collaboration
• Leadership
• Creativity
• Scientific Writing
• Project Management
• Continuous Learning

Career Growth

• Senior Cybersecurity Research Scientist
• Principal Research Scientist
• Distinguished Security Researcher
• Security Architect
• AI Security Architect
• Director of Cybersecurity Research
• Chief Security Scientist
• Chief Information Security Officer (CISO

Job Description

We are seeking an experienced AI Ethics & Responsible AI Specialist to help ensure that our artificial intelligence and machine learning solutions are developed, deployed, and governed responsibly. This role is responsible for establishing ethical AI practices, assessing AI risks, and implementing governance frameworks that promote fairness, transparency, accountability, privacy, and regulatory compliance across AI initiatives.

The ideal candidate will work closely with AI Engineers, Data Scientists, Product Managers, Legal, Security, Privacy, and Compliance teams to evaluate AI systems throughout their lifecycle. You will help identify and mitigate algorithmic bias, improve model explainability, develop AI governance policies, and ensure compliance with emerging AI regulations and industry standards.

This position requires a strong understanding of machine learning, AI governance, risk management, data privacy, and ethical AI principles, along with the ability to communicate complex technical and regulatory concepts to both technical and business stakeholders.

Key Responsibilities

• Develop and maintain Responsible AI governance frameworks, policies, and standards.
• Conduct AI risk assessments throughout the AI and machine learning lifecycle.
• Evaluate AI models for fairness, bias, transparency, robustness, explainability, and accountability.
• Collaborate with AI Engineering and Data Science teams to implement ethical AI best practices.
• Perform algorithmic bias testing and recommend mitigation strategies.
• Ensure compliance with AI regulations, privacy laws, and industry standards.
• Develop AI model documentation, model cards, and governance reports.
• Support AI audits, regulatory assessments, and internal compliance reviews.
• Establish AI monitoring processes for model performance, drift, fairness, and compliance.
• Work with Legal, Privacy, Security, and Risk teams to evaluate AI-related risks.
• Define AI governance controls for Generative AI, Large Language Models (LLMs), and AI-powered products.
• Promote responsible data collection, usage, and retention practices.
• Deliver Responsible AI awareness sessions and training programs for technical and business teams.
• Research emerging AI regulations, governance frameworks, and ethical AI trends.
• Recommend continuous improvements to strengthen organizational AI governance and compliance.

Required Qualifications

• Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Information Systems, Cybersecurity, Ethics, Public Policy, Law, or a related field.
• 3–6+ years of experience in AI governance, Responsible AI, machine learning, data science, risk management, cybersecurity, compliance, or technology governance.
• Strong understanding of machine learning concepts and AI development lifecycle.
• Experience with AI governance frameworks, AI risk management, or model governance.
• Knowledge of AI fairness, explainability, model validation, and algorithmic bias mitigation techniques.
• Familiarity with AI regulations, data privacy requirements, and enterprise compliance programs.
• Excellent communication, analytical, documentation, and stakeholder management skills.
• Experience working with cross-functional teams in enterprise environments.

Preferred Qualifications

• Master's degree in Artificial Intelligence, Data Science, Computer Science, Public Policy, Ethics, or a related field.
• Experience with Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG).
• Experience supporting AI governance for cloud-based AI platforms.
• Familiarity with AI model lifecycle management and MLOps.
• Knowledge of enterprise risk management and cybersecurity governance.
• Experience participating in AI ethics committees or governance boards.

Preferred Technical Skills

• Python
• SQL
• Machine Learning
• Deep Learning
• Generative AI
• Large Language Models (LLMs)
• Prompt Engineering
• Retrieval-Augmented Generation (RAG)
• LangChain
• Hugging Face Transformers
• TensorFlow
• PyTorch
• Scikit-learn
• MLflow
• AI Governance
• Responsible AI
• Model Risk Management
• AI Fairness & Bias Detection
• Explainable AI (XAI)
• AI Model Validation
• Data Privacy
• Risk Assessment
• Governance, Risk & Compliance (GRC)
• AWS
• Microsoft Azure
• Google Cloud Platform (GCP)
• Git
• Docker
• Kubernetes

Preferred Certifications

• Microsoft Certified: Azure AI Engineer Associate
• Google Professional Machine Learning Engineer
• AWS Certified Machine Learning – Specialty
• Certified Information Systems Security Professional (CISSP)
• Certified Information Security Manager (CISM)
• ISO/IEC 42001 AI Management Systems (awareness or lead implementer)
• NIST AI Risk Management Framework (AI RMF) knowledge
• Certified Data Privacy Solutions Engineer (CDPSE)

Job Description

We are seeking a highly analytical and results-driven Customer Analytics Data Scientist to join our growing Data Science team. In this role, you will leverage advanced analytics, machine learning, and statistical modeling to understand customer behavior, improve customer experiences, and drive strategic business decisions. You will work closely with Product, Marketing, Sales, Customer Success, and Engineering teams to transform large datasets into actionable insights that enhance customer acquisition, engagement, retention, and lifetime value.

The ideal candidate has strong expertise in predictive analytics, customer segmentation, recommendation systems, experimentation, and data visualization. You should be proficient in Python, SQL, machine learning, and cloud-based analytics platforms, with the ability to communicate complex analytical findings to both technical and non-technical stakeholders.

Key Responsibilities

• Analyze large-scale customer data to identify trends, behaviors, and business opportunities.
• Develop predictive models for customer acquisition, retention, churn prediction, and lifetime value (CLV).
• Build customer segmentation models using clustering and behavioral analytics techniques.
• Design, execute, and evaluate A/B tests and multivariate experiments to optimize customer experiences.
• Develop recommendation systems and personalization models to improve customer engagement.
• Create forecasting models for customer demand, revenue, and marketing performance.
• Collaborate with Product, Marketing, Sales, and Customer Success teams to support data-driven decision-making.
• Design interactive dashboards and reports using business intelligence tools.
• Build and maintain scalable data pipelines for analytics and machine learning workflows.
• Apply statistical analysis and hypothesis testing to validate business initiatives.
• Monitor model performance, accuracy, and business impact, making improvements as needed.
• Ensure data quality, governance, privacy, and compliance with organizational policies.
• Present analytical findings and strategic recommendations to business leaders and executive stakeholders.
• Stay current with emerging technologies, machine learning techniques, and customer analytics best practices.

Required Qualifications

• Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Economics, Information Systems, or a related field.
• 3–5+ years of experience in data science, customer analytics, business analytics, or predictive modeling.
• Strong programming experience with Python and SQL.
• Experience with machine learning frameworks such as Scikit-learn, TensorFlow, or PyTorch.
• Solid understanding of statistics, predictive modeling, clustering, classification, regression, and time-series analysis.
• Experience working with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP).
• Familiarity with ETL processes, data warehousing, and big data technologies.
• Excellent analytical thinking, problem-solving, and communication skills.
• Ability to explain technical concepts and analytical insights to non-technical audiences.

Preferred Qualifications

• Master's degree in Data Science, Statistics, Computer Science, Business Analytics, or a related field.
• Experience with customer relationship management (CRM) analytics.
• Knowledge of recommendation engines and personalization algorithms.
• Experience with marketing analytics and digital customer journey analysis.
• Familiarity with MLOps tools and model deployment pipelines.
• Experience working in e-commerce, SaaS, fintech, retail, healthcare, or consumer technology industries.

Preferred Technical Skills

• Python
• SQL
• R
• Pandas
• NumPy
• Scikit-learn
• TensorFlow
• PyTorch
• Apache Spark
• Databricks
• Snowflake
• Tableau
• Power BI
• Looker
• Google Analytics 4 (GA4)
• Customer Data Platforms (CDPs)
• CRM Analytics
• Machine Learning
• Predictive Analytics
• Customer Segmentation
• Churn Prediction
• Customer Lifetime Value (CLV)
• Recommendation Systems
• A/B Testing
• Statistical Analysis
• Data Visualization
• Feature Engineering
• AWS
• Microsoft Azure
• Google Cloud Platform (GCP)
• Git
• Docker