Software Engineer II - Data Engineer/applied AI (llms)

JPMorgan Chase JPMorgan Chase · Banking · Plano, TX +1 · Asset & Wealth Management

Software Engineer II - Data Engineer/Applied AI (LLMs) role at JPMorgan Chase, focusing on building an agentic production data platform using LLMs. The role involves designing, developing, and deploying AI-first solutions, including agents and leveraging tools like Claude Code and RAG. Requires hands-on experience with AI-assisted development tools and understanding of responsible AI practices within a financial services context.

What you'd actually do

  1. Designs, develops, codes, and troubleshoots with consideration of upstream and downstream systems and technical implications
  2. Hands on design and development of agentic production data platform with full stack application ownership.
  3. AI first mindset in developing code using Claude Code, building agents to make application/platform autonomous.
  4. Develop AI skills, agents, MCP server in support of product capabilities to deliver business value
  5. 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

Skills

Required

  • React or Angular with TypeScript
  • Python, Java, or Kotlin with REST or GraphQL
  • Spark, Kafka, Airflow, Snowflake, and AWS
  • containers, CI/CD, observability, and controlled release practices
  • Claude Code, Agent, Skills, RAG, embeddings, prompt or configuration management, evaluation and guardrails, and agent tool or function calling

Nice to have

  • financial services or Wealth Management experience
  • data governance or data management domain expertise
  • experience evaluating and enterprise-hardening open-source software
  • Advanced degree

What the JD emphasized

  • Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, testing, troubleshooting, or documentation) with demonstrated ability to critically evaluate and validate AI-generated outputs.
  • Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations.
  • Applied AI with LLMs: Claude Code, Agent, Skills, RAG, embeddings, prompt or configuration management, evaluation and guardrails, and agent tool or function calling

Other signals

  • Hands on design and development of agentic production data platform with full stack application ownership.
  • AI first mindset in developing code using Claude Code, building agents to make application/platform autonomous.
  • Develop AI skills, agents, MCP server in support of product capabilities to deliver business value
  • Applied AI with LLMs: Claude Code, Agent, Skills, RAG, embeddings, prompt or configuration management, evaluation and guardrails, and agent tool or function calling