Key Responsibilities

• Design and implement AI and Generative AI solutions.
• Build RAG, Agentic AI, and LLM-based applications.
• Develop ML models for prediction, recommendation, and analytics.
• Manage AI platforms on AWS, GCP, and Azure.
• Implement MLOps, CI/CD, model monitoring, and deployment pipelines.
• Lead and mentor AI/ML engineering teams.
• Collaborate with stakeholders to drive AI transformation projects.

Required Skills

• Generative AI & LLMs (GPT-4, Claude, LLaMA, Gemini)
• RAG / Agentic AI
• LangChain, LangGraph, LlamaIndex
• Python, SQL, PyTorch, TensorFlow
• AWS, GCP, Azure
• Kubernetes, Docker, MLflow, Kubeflow
• Vector Databases (FAISS, ChromaDB)

Preferred Certifications

• AWS Machine Learning Specialty
• Google Professional ML Engineer
• Microsoft Azure Data Scientist Associate

Education

Bachelor’s or Master’s Degree in Computer Science, AI, Data Science, or related field.