Software Engineer III - Agentic AI

JPMorgan Chase JPMorgan Chase · Banking · Bengaluru, Karnataka, India · Consumer & Community Banking

Software Engineer III role focused on building agentic AI solutions within a large enterprise environment. Requires proficiency in Python/Java, system design, cloud technologies (AWS), and containerization. Familiarity with agent frameworks (LangGraph, Autogen), LLM evaluation tools, and model training/inference technologies is preferred.

What you'd actually do

  1. Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
  2. Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
  3. Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
  4. Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
  5. Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture

Skills

Required

  • Formal training or certification on software engineering concepts and 3+ years applied experience
  • Hands-on practical experience in system design, application development, testing, and operational stability
  • Proficient in coding in one or more languages - Python/ Java
  • Concepts like / Microservices / RestAPIs / Spring Boot
  • Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
  • Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
  • Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
  • Experience with Cloud based Technologies (AWS) and Relational Databases (Oracle) or No-SQL Databases, Terraform
  • Experience in containerization technologies - Docker, Kubernetes etc

Nice to have

  • Familiarity with building ML/Gen AI/LLM based/Agentic solutions, CI/CD pipelines for the same
  • Familiarity with tools & technologies like Google Agent Development Kit (ADK)/LangGraph/LangChain/Autogen/Rasa CALM, A2A protocol, MCP protocol
  • Familiarity with tools like Arize Phoenix/Nemo Guardrails/Lang Smith/Galileo
  • Familiarity with LLM/Agent evaluation solutions like Ragas/Deepeval/LLM as Judge etc
  • Familiarity with model training & inferencing technolgoies like - vLLM/ Nvidia Triton Inference engine/Ray Serve, TensorRT LLM, Pytorch, Huggingface, Tensorflow, ONNX, OpenAI Triton library, CUDA
  • Exposure to AWS cloud technologies

What the JD emphasized

  • building ML/Gen AI/LLM based/Agentic solutions
  • Familiarity with building ML/Gen AI/LLM based/Agentic solutions

Other signals

  • building agentic AI solutions
  • experience with agent frameworks
  • familiarity with LLM/Agent evaluation