Data Engineer III: AI & LLMs Platform Engineer

JPMorgan Chase & Co.

Plano (TX)

On-site

USD 120,000 - 180,000

Full time

14 days+

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Job summary

JPMorgan Chase & Co. is seeking a Data Engineering & Applied AI Software Engineer III within the Asset & Wealth Management division.

You will be a core contributor on an agile team, building secure, scalable tech products that support the firm's business objectives. You will design and develop a production data platform, apply AI-assisted coding practices, and work with Spark, Kafka, Airflow, Snowflake, and AWS to deliver reliable solutions.

Qualifications

Formal training or certification in software engineering with 3+ years of applied experience.
Hands-on experience using enterprise AI-assisted development tools with ability to evaluate outputs.
Understanding of responsible AI use, data sensitivity, secure handling, resiliency and security.
Frontend: React or Angular with TypeScript.
Backend: Python, Java, or Kotlin with REST or GraphQL.
Data engineering: Spark, Kafka, Airflow, Snowflake, AWS.
Platform engineering: containers, CI/CD, observability, controlled release.
Applied AI with LLMs: Claude Code, Agent, Skills, RAG, embeddings, guardrails, tool or function calling.

Responsibilities

Executes standard software solution, design, development, and technical troubleshooting.
Leverages enterprise AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity, while validating outputs through peer review, automated testing, and secure coding standards.
Designs, develops, codes, and troubleshoots with consideration of upstream and downstream systems and technical implications.
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.
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.
Applies technical troubleshooting to breakdown solutions and solve technical problems of basic complexity.
Gathers, analyzes, and draws conclusions from large, diverse data sets to identify problems and contribute to decision‑making in service of secure, stable application development.
Learns and applies system processes, methodologies, and skills for the development of secure, stable code and systems.