GenAI / Agentic AI Engineer
Infosys · Bengaluru · onsite · Posted 33d ago
Undisclosed5–10 yrsfulltimeSourced from
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About this role
Job 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
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
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
Sourced from naukri
Skills
QADevopsDockerRetrieval Augmented GenerationBedrockclaudeCI/CD Pipelinesworkflowsapisaws bedrockpytestamazon web servicesOOPenterprise applicationsai engineerEmbeddingsfixturesRAG PipelinesPythonLangchainGenerative AiGITData ScienceArtificial Intelligence
About Infosys

Infosys
IT Services & Consulting
323.6k+
employees
1981
45 years old
Bengaluru/Bangalore, Karnataka
India
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