Lead Software Engineer - Test Automation

Company: JPMorganChase

Location: Chicago, IL 60603

Salary: $133,000 - $185,000 a year

Type: Full-time

Posted: 2026-04-30

About this role

JOB DESCRIPTION

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

As a Lead Software Engineer at JPMorgan Chase within the Commercial & Investment Bank, 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 will be responsible for designing and executing test strategies for AI-driven chat solutions. You’ll build and maintain automation frameworks, integrate tests into CI/CD pipelines, and validate AI/ML models for fairness and performance. The role demands strong leadership, adaptability, and deep knowledge of software development, agile methodologies, and financial services technology. Preferred skills include experience with large language models, prompt engineering, accessibility testing, and database technologies

Job responsibilities

  • The role will involve quality and test advocacy and the individual will need to have hands on Quality Engineering and test automation experience, as well as strong lead skills.
  • Stay current with advancements in AI, test automation, and quality engineering, and proactively introduce innovative tools and practices to the team.
  • High level of flexibility and ability to react quickly to changing business needs in a fast-paced environment driven by market pressures.
  • The position will be accountable for large projects of high complexity, high risk and high visibility.
  • Design, implement, and execute test plans and test cases specifically targeting AI-driven conversational flows, natural language understanding (NLU), and machine learning model outputs.
  • Integrate automated tests into CI/CD pipelines to enable rapid, reliable, and repeatable validation of new features and bug fixes.
  • Validate AI/ML models, ensuring they meet functional and non-functional requirements, including fairness, bias mitigation, ...

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