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.

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.

Technical Requirements

Must-Have Skills

- 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

Additional Responsibility

- Experience: 5-15 Years
- Locations: Bangalore | Chennai | Pune | Hyderabad | Trivandrum
- Employment: Full time
- Educational Requirement: MCA,MSc,MTech,Bachelor of Engineering,BTech
- Preferred Skills: Technology->AI-AI Engineering->AI/ML Solution Architecture and Design->traditional ai ml
- Service Line: Data Analytics Unit

📌 AI/ML Developer (Bengaluru)
🏢 Infosys
📍 Bengaluru