Overview

• We are looking for experienced AI ML Engineers who can build and productionize enterprise grade Machine Learning Generative AI and Agentic AI solutions • The ideal candidate will combine strong Python and Machine Learning fundamentals with hands on experience in AWS AI ML services Retrieval Augmented Generation RAG LLM integration and agentic workflows • You should be comfortable taking solutions from experimentation and model development through deployment evaluation monitoring and production operations • This is a hands on engineering role for professionals who have built real ML GenAI sol

Responsibilities

• Design and deploy end to end ML and Generative AI pipelines on AWS using Amazon SageMaker and Amazon Bedrock
• Build intelligent LLM powered agents and Agentic AI workflows using LangGraph and or LangChain
• Architect production ready RAG solutions covering document ingestion chunking embeddings metadata vector indexing retrieval and response generation
• Develop and productionize ML models for use cases such as forecasting recommendations prediction and customer analytics
• Integrate foundation models and LLM APIs including Amazon Bedrock and OpenAI into scalable enterprise applications
• Engineer robust prompting context management and tool calling orchestration workflows for LLM applications
• Implement LLM evaluation grounding hallucination mitigation and responsible AI guardrails
• Build semantic and hybrid retrieval solutions with vector search technologies such as FAISS Pinecone and OpenSearch
• Apply MLOps LLMOps principles for model and application deployment versioning evaluation monitoring and lifecycle management
• Develop scalable Python based APIs and services to expose AI ML capabilities to downstream applications
• Collaborate with data engineers architects product teams and cloud platform engineers to move AI solutions from prototype to production
• The emphasis on RAG construction evaluation production agents vector indexing and LangGraph LangChain closely reflects recent Infosys internal AI engineering requiremen
• Must Have Skills
• Candidates should have strong hands on experience in most of the following
• Programming ML
• Strong Python
• Scikit learn
• TensorFlow and or PyTorch
• Machine Learning model development and production deployment
• ML pipelines and MLOps concepts
• Generative AI Agentic AI
• Generative AI LLM application development
• LangGraph and or LangChain
• Agentic AI AI Agents
• Retrieval Augmented Generation RAG
• Prompt Engineering
• Embeddings and semantic retrieval
• LLM evaluation and grounding techniques
• Tool function calling and agent orchestration
• AWS