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.
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
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
Experience: 5–15 Years
Locations: Bangalore | Chennai | Pune | Hyderabad | Trivandrum
Employment: Full-time
Source: Infosys careers — Read the original posting and apply
This role is listed by the employer on its own careers site. Kaam Ki Khoj does not process applications for it.
Infosys is an employer in the IT/Computers - Software, Software Services sector with operations in India. This is a directory listing maintained by Kaam Ki Khoj so that candidates can find the organisation; it is not an official company page and Kaam... Read More
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