GenAI / Agentic AI Engineer

Infosys; Bengaluru; On-site; INR 1,200,000 - 2,600,000; Full time

Job summary

Infosys is recruiting a GenAI Engineer to build Python-based GenAI features and AI workflows.

You'll work with AWS Bedrock models, Lambdas, and LangChain, crafting robust RAG pipelines and agent flows while ensuring quality with CI/CD and testing. Collaboration with architects and QA is essential.

Qualifications

• Must have strong Python fundamentals for GenAI workflows.
• Experience with OOP, typing, modules and testing frameworks.
• Familiarity with AWS Bedrock model invocation and prompt engineering.
• Understanding of retrieval-augmented generation (RAG) and knowledge bases.
• Knowledge of LangChain/LangGraph and basic agent flows.
• Exposure to DevOps basics: Git, CI/CD, and Docker.

Responsibilities

• Develop GenAI features and workflows using Python and AWS Bedrock.
• Implement RAG pipelines including chunking, embeddings, and retrieval.
• Build single/multi-step agent workflows with LangChain/LangGraph.
• Integrate LLMs with APIs, tools, and enterprise apps.
• Write tested Python code with CI/CD pipelines.
• Monitor latency, token usage, and cost metrics.
• Collaborate with architects, seniors, and QA teams.

Skills

Python

OOP

Typing

Modules

pytest

unittest

Fixtures

Async

Guardrails

Access controls

Prompting

RAG

LangChain

LangGraph

Agent flows

Routing

Knowledge bases

Retrieval

Git

CI/CD

Docker

APIs

Artifacts

Tools

AWS Bedrock

LangChain

LangGraph

Git

CI/CD

Docker

APIs

Retrieval systems

Job description

Must Have Skills Python - Core concepts: OOP, typing, modules, pytest/unittest, fixtures, basic async AWS Bedrock - Model invocation (Claude/Titan, etc.), Knowledge bases or retrieval integration, basic understanding of guardrails & access controls Generative AI - Prompting (system, few-shot), RAG types and approaches, Basic evaluation awareness, LangChain / LangGraph , Simple agent flows and routing DevOps Basics - Git, PRs, CI pipelines, Docker basics, artifacts _______________________________________

Key Responsibilities

• Develop GenAI features and workflows using Python and AWS Bedrock
• Implement RAG pipelines (chunking, embeddings, retrieval, grounding)
• Build single/multi-step agent workflows using LangChain / LangGraph
• Integrate LLMs with APIs, tools, and enterprise applications
• Write tested, maintainable Python code with CI/CD pipelines
• Monitor basic latency, token usage, and cost metrics
• Collaborate with architects, seniors, and QA teams