Software Engineer III - Python Developer + Aws + 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, leveraging AI coding assist tools, building data pipelines, and developing solutions using AI agent frameworks like Langchain and LangGraph for document-based Gen AI use cases. Requires strong Python expertise and experience with LLMs, Gen AI solution integration, and RAG solutions.

What you'd actually do

  1. Executes software solutions which integrate Gen AI models with Enterprise workflows, including design, development, and technical troubleshooting. Demonstrates the ability to think beyond routine or conventional approaches to build solutions or break down technical problems
  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. Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
  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
  • enterprise-authorized AI-assisted software development tools
  • responsible AI use
  • LLMs
  • Gen AI solution integration
  • RAG solutions
  • system design
  • application development
  • building data pipelines
  • testing
  • operational stability
  • AI agents frameworks
  • Langchain
  • LangGraph
  • document-based Gen AI use cases
  • Python programming
  • ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face)
  • developing, debugging, and maintaining code in a large corporate environment
  • modern programming languages
  • database querying languages
  • cloud-based AI services (e.g., AWS, Azure, or GCP)
  • agile methodologies
  • application resiliency
  • security
  • CI/CD pipelines
  • software applications and technical processes within ML and Cloud technologies
  • Software Development Life Cycle

Nice to have

  • building Gen AI solutions for the enterprise
  • Java
  • shell scripting
  • AWS/similar cloud technologies
  • Certifications in cloud technologies

What the JD emphasized

  • Python is a must-have
  • Hands-on experience using enterprise-authorized AI-assisted software development tools
  • Understanding of responsible AI use in engineering workflows
  • Software development experience and working experience with LLMs, Gen AI solution integration, RAG solutions.
  • Experience in AI agents frameworks, Langchain, and LangGraph.

Other signals

  • integrates Gen AI models with Enterprise workflows
  • Leverages enterprise-authorized AI coding assist tools
  • Builds data pipelines
  • Experience in AI agents frameworks, Langchain, and LangGraph
  • document-based Gen AI use cases