AI/ML Developer

Job Description:

• 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 solutions rather than only experimented with LLM APIs

Key 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

Technical Requirements:

• 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
• Amazon Bedrock
• Amazon SageMaker
• Experience deploying AI ML workloads within AWS environments
• LLM Integration
• Amazon Bedrock model integration and or OpenAI APIs
• Foundation model integration
• API driven GenAI applications
• Vector Search Databases
• FAISS
• Pinecone
• OpenSearch
• Or comparable vector database retrieval technology
• Recent Infosys AI hiring material similarly highlights LangGraph LangChain RAG Pinecone FAISS type vector stores prompt engineering evaluation and production AI engineering

Additional Responsibilities:

• Experience 5 15 Years
• Locations Bangalore Chennai Pune Hyderabad Trivandrum
• Employment Full time

Preferred Skills:

Technology->AI-AI Engineering->AI/ML Solution Architecture and Design->traditional ai ml