AI Engineer

Job Summary

We are seeking an innovative AI Engineer to design, develop, and deploy scalable Artificial Intelligence and Machine Learning solutions that drive business innovation and operational efficiency. The ideal candidate will have hands-on experience building production-ready AI applications, integrating Large Language Models (LLMs), and developing machine learning pipelines using modern cloud technologies. You will collaborate with Data Scientists, Software Engineers, Product Managers, and DevOps teams to build intelligent systems that solve complex business challenges.

Key Responsibilities

• Design, develop, and deploy AI and Machine Learning models for production environments.
• Build scalable AI applications using Large Language Models (LLMs), Natural Language Processing (NLP), and Generative AI technologies.
• Develop Retrieval-Augmented Generation (RAG) pipelines and AI-powered chatbots.
• Fine-tune, evaluate, and optimize machine learning and deep learning models.
• Create and maintain end-to-end ML pipelines for data preprocessing, model training, deployment, and monitoring.
• Integrate AI models with enterprise applications through REST APIs and microservices.
• Collaborate with Data Scientists to productionize research models.
• Optimize AI model performance, inference speed, and operational costs.
• Implement MLOps best practices for continuous integration, deployment, and monitoring of AI systems.
• Work with cloud-native AI services across AWS, Microsoft Azure, and Google Cloud Platform.
• Ensure AI solutions follow security, privacy, governance, and responsible AI best practices.
• Stay current with emerging AI technologies, frameworks, and industry trends.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field.
• 3–6+ years of experience in Artificial Intelligence, Machine Learning, or Software Engineering.
• Experience developing and deploying AI applications in production environments.
• Strong understanding of machine learning algorithms, deep learning, and statistical modeling.
• Experience with cloud platforms and containerized deployments.
• Excellent analytical, problem-solving, and communication skills.

Required Technical Skills

• Python
• SQL
• Machine Learning
• Deep Learning
• TensorFlow
• PyTorch
• Scikit-learn
• Pandas
• NumPy
• Hugging Face Transformers
• OpenAI API
• LangChain
• LlamaIndex
• Retrieval-Augmented Generation (RAG)
• Prompt Engineering
• Vector Databases (Pinecone, Weaviate, FAISS, ChromaDB)
• FastAPI
• REST APIs
• Docker
• Kubernetes
• Git
• MLflow
• Apache Spark
• AWS (SageMaker, Lambda, EC2, S3)
• Microsoft Azure AI Services
• Google Cloud Vertex AI

Preferred Qualifications

• Experience building AI copilots, virtual assistants, or intelligent automation solutions.
• Familiarity with multimodal AI, computer vision, or speech AI.
• Experience implementing MLOps pipelines using Kubeflow or Azure ML.
• Knowledge of responsible AI, model evaluation, and AI governance.
• Experience with CI/CD pipelines and DevOps practices.
• Familiarity with Agile or Scrum development methodologies.

Preferred Certifications

• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure AI Engineer Associate (AI-102)
• Microsoft Certified: Azure Data Scientist Associate (DP-100)
• Google Professional Machine Learning Engineer
• TensorFlow Developer Certificate
• Databricks Certified Machine Learning Professional

Benefits

• Competitive salary with annual performance bonuses.
• Medical, dental, and vision insurance.
• Flexible remote and hybrid work options.
• Paid vacation, holidays, and parental leave.
• Professional development and certification reimbursement.
• Employee wellness programs.
• Stock options or equity (where applicable).
• Career growth and leadership opportunities.