Responsibilities :

Design/deploy ML pipelines and LLM-powered agents (RAG, Agentic AI) using AWS Bedrock, SageMaker, LangGraph

Develop, train, and productionize ML models (churn, recommendation, forecasting) with MLOps practices

Build RAG architectures, integrate LLM APIs, prompt engineering, and responsible AI guardrails

Strong Python (Scikit-learn, TensorFlow, PyTorch) hands-on SageMaker vector DBs (FAISS, Pinecone, OpenSearch)

Must-have: Python, LangGraph/LangChain, Bedrock/OpenAI integration | Nice-to-have: LLM fine-tuning, LangSmith/W&B;, AWS ML Specialty

Technical and Qualified Requirements:

Robust proficiency in Python and AI/ML libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch.



Hands-on experience with Generative AI and Large Language Models (LLMs). Experience with OpenAI, Claude, Gemini, Llama, or similar foundation models. Strong understanding of Prompt Engineering, RAG, Embeddings, and Vector Databases. Experience with LangChain, LangGraph, LlamaIndex, or similar frameworks. Hands-on experience with AWS Services such as: SageMaker Bedrock Lambda EC2 S3 Glue API Gateway CloudWatch Solid SQL and data processing skills. Experience with REST APIs and microservices architecture. Knowledge of Git, CI/CD, and Agile methodologies.

📌 Ai/ml Engineer Generative Ai, Ml,aws Bengaluru
🏢 Infosys
📍 Bengaluru