Software Engineer III - Python Developer + LLM / Gen AI

JPMorgan Chase JPMorgan Chase · Banking · Bengaluru, Karnataka, India · Commercial & Investment Bank

Software Engineer III role focused on integrating Gen AI models with enterprise workflows and building agentic workflows using LLMs, RAG, and frameworks like Langchain. The role involves designing, developing, and troubleshooting AI solutions, leveraging AI coding assist tools, building data pipelines, and creating secure production code. Requires strong Python expertise and experience with AI agent frameworks.

What you'd actually do

  1. Executes software solutions which integrate Gen AI models with Enterprise workflows, including design, development, and technical troubleshooting.
  2. Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.
  3. Design and built Agentic workflows to automate business processes; design end user experiences with HITL.
  4. Builds data pipelines that clean, transform, and aggregate data from disparate sources.
  5. Creates secure and high-quality production code and maintains algorithms that integrate seamlessly with appropriate systems.

Skills

Required

  • Python
  • Python frameworks like Django, Flask or FastAPI
  • LLMs
  • Gen AI solution integration
  • RAG solutions
  • system design
  • application development
  • building data pipelines
  • testing
  • operational stability
  • AI agents frameworks
  • Google ADK
  • Langchain
  • MCP
  • Agentic AI use cases
  • developing, debugging, and maintaining code
  • modern programming languages
  • database querying languages
  • enterprise-authorized AI-assisted software development tools
  • responsible AI use
  • data sensitivity considerations
  • secure handling of inputs/outputs
  • resiliency and security expectations
  • Software Development Life Cycle
  • agile methodologies
  • application resiliency
  • security
  • CI/CD pipelines
  • ML technologies
  • Cloud technologies

Nice to have

  • building Gen AI Agentic solutions for the enterprise
  • building solutions using AWS/similar cloud technologies
  • Certifications in AI & Cloud technologies

What the JD emphasized

  • Python is a must-have
  • working experience with LLMs, Gen AI solution integration, RAG solutions
  • Experience in AI agents frameworks, Google ADK, Langchain, MCP
  • Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment

Other signals

  • integrates Gen AI models with Enterprise workflows
  • Design and built Agentic workflows
  • working experience with LLMs, Gen AI solution integration, RAG solutions
  • Experience in AI agents frameworks, Google ADK, Langchain, MCP