GenAI / Agentic AI Engineer

TymblHub; Bengaluru; On-site; INR 540,000 - 790,000; Full time

Job summary

Infosys Limited in Bengaluru is seeking an AI Engineer to build GenAI features and production-ready AI workflows using Python and AWS Bedrock under senior guidance.

You will implement RAG pipelines, integrate with APIs and enterprise apps, and contribute to CI/CD and monitoring of latency and costs, collaborating with architects, seniors, and QA teams.

Qualifications

• Python core concepts: OOP, typing, modules, pytest/unittest, fixtures, basic async.
• AWS Bedrock model invocation and retrieval integration.
• GenAI prompting, RAG types and approaches.
• LangChain / LangGraph and simple agent flows.
• Git, PRs, CI pipelines, Docker basics.

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.

Skills

Python

AWS Bedrock

Generative AI

LangChain

LangGraph

RAG pipelines

Git

CI/CD

Docker

API integration

Education

Bachelor of Engineering

Job description

# GenAI / Agentic AI EngineerInfosys LimitedPosted on October 22, 2026---Experience5 - 10 yrsSalary (CTC)₹5.4L - ₹7.9LJob LocationBengaluru, IndiaVacancy1DesignationAI EngineerJob TypeNot specified---## Job DescriptionJob DescriptionRole Purpose Hands on engineer to build Python based GenAI and AWS Bedrock solutions, contributing to RAG pipelines, agent workflows, and production-ready AI features under senior guidance. Roles ResponsibilitiesKey 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 Technical RequirementMust 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 \\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_ Educational RequirementBachelor of Engineering Preferred SkillsTechnology->AI-Data science->PYTHON,Technology->AI-Generative AI->Generative AI - Basic->retrieval augmented generation (rag) Service LineTopaz COE unit