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

JPMorganChase; Plano (TX); On-site; USD 120,000 - 160,000; Full time

Job summary

JPMorganChase in Plano, TX is seeking a Data Engineering & Applied AI Software Engineer III to join an agile team delivering trusted, scalable technology products in Asset & Wealth Management. You will build and extend data platforms, apply AI-assisted development tools, and own end-to-end code quality from design through production, with a strong emphasis on secure, reliable software delivery.

Collaborate across teams to turn large data sets into insights while adhering to enterprise standards.

Qualifications

• Formal training or certification in software engineering concepts.
• Experience using enterprise AI-assisted development tools.
• Understanding responsible AI use in engineering workflows.

Responsibilities

• Writes secure, high-quality code with limited guidance.
• Uses AI-assisted tools to improve coding speed and quality.
• Designs and troubleshoots with consideration of upstream/downstream systems.
• Gathers and analyzes large data sets to inform decisions.

Skills

Software engineering

AI-assisted development

Data pipelines

Secure coding

Code review

Education

Software engineering training

Tools

Claude Code

AI coding tools

Job description

Job Description

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Data Engineering & Applied AI Software Engineer III 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 3+ 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