Software Engineer II - Data Engineer/Applied AI (LLMs)

JPMorgan Chase & Co.; Plano (TX); On-site; USD 120,000 - 180,000; Full time

Job summary

JPMorganChase within Asset & Wealth Management is seeking a Data Engineering & Applied AI Software Engineer II. You will join an agile team building trusted, scalable data platforms and AI-enabled products.

Focus areas include secure code development, AI-assisted tooling, and end-to-end data workflows across Spark, Kafka, Airflow, Snowflake, and AWS. Responsibilities cover design, development, troubleshooting, and integration with upstream/downstream systems, plus hands-on work on agentic data

Qualifications

• Formal training or certification on software engineering concepts and 2+ years applied experience.
• Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations.
• Frontend: React or Angular with TypeScript.
• Backend: Python, Java, or Kotlin with REST or GraphQL.
• Data Engineering/Platform: Spark, Kafka, Airflow, Snowflake, and AWS.
• Platform engineering: containers, CI/CD, observability, and controlled release practices.
• Applied AI with LLMs: Claude Code, Agent, Skills, RAG, embeddings, prompt or configuration management, evaluation and guardrails, and agent tool or function calling

Responsibilities

• Executes standard software solution, design, development, and technical troubleshooting
• Writes secure and high-quality code using the syntax of at least one programming language with limited guidance
• Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity (e.g., code generation/refactoring, unit test creation, documentation), 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

Skills

React/Angular

TypeScript

Python

Java

Kotlin

REST

GraphQL

Spark

Kafka

Airflow

Snowflake

AWS

Containers

CI/CD

Observability

Release practices

Claude Code

Agent Tool Calling

RAG

Embeddings

Prompt management

AI-assisted development

Responsible AI

Education

Bachelor's degree

Advanced degree

Tools

Jenkins

Spark SQL

Job description

You're ready to gain the skills and experience needed to grow within your role and advance your career - and we have the perfect software engineering opportunity for you.

As a Data Engineering & Applied AI Software Engineer II at JPMorganChase within the Asset & Wealth Management, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives.

Job responsibilities

• Executes standard software solution, design, development, and technical troubleshooting
• Writes secure and high-quality code using the syntax of at least one programming language with limited guidance
• Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity (e.g., code generation/refactoring, unit test creation, documentation), 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

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 2+ years applied experience
• 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.
• Frontend: React or Angular with TypeScript.
• Backend: Python, Java, or Kotlin with REST or GraphQL.
• Data Engineering/Platform: Spark, Kafka, Airflow, Snowflake, and AWS.
• Platform engineering: containers, CI/CD, observability, and controlled release practices.
• Applied AI with LLMs: Claude Code, Agent, Skills, RAG, embeddings, prompt or configuration management, evaluation and guardrails, and agent tool or function calling

Preferred qualifications, capabilities, and skills

• Preferred financial services or Wealth Management experience, data governance or data management domain expertise, and experience evaluating and enterprise-hardening open-source software
• Bachelor's degree required. Advanced degree is a plus