Senior Lead Software Engineer - Precious Metals / Front Office / Athena

JPMorgan Chase JPMorgan Chase · Banking · New York, NY +1 · Commercial & Investment Bank

Senior Lead Software Engineer role focused on enhancing and building technology products for the Precious Metals and Agriculture Commodities Tech team at JPMorgan Chase. The role involves leading a software engineering team, driving adoption of AI-assisted engineering practices, developing secure code, and collaborating with business and technology teams. Experience with enterprise-authorized AI-assisted tools and responsible AI use is required.

What you'd actually do

  1. Works closely with Trading, Quantitative Research, Sales and Middle Office teams to deliver quality code in a fast paced environment
  2. Acts as the regional lead for the Precious Metals and Agricultural products team supporting the regional needs of the precious metals business while remaining aligned with the global team and global priorities.
  3. Acts as the direct manager for the NYC based software engineering team, helping drive business results through the team
  4. Drives adoption and governance of approved AI assisted engineering practices across teams to improve code quality, deliver speed, and operation outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patters and automation within the SDLC/TLM toolchain
  5. Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale

Skills

Required

  • Formal training or certification on software engineering concepts and 5+ years applied experience
  • 2+ years of experience leading technologists to manage and solve complex technical items within your domain of expertise
  • Degree in Computer Science, Information Systems, Math or equivalent training and relevant experience
  • Hands-on practical experience delivering system design, application development, testing, and operational stability
  • Experience in performant, large-scale system development in an object-oriented or functional language such as Python, Java, etc.
  • Advanced knowledge of software applications and technical processes with considerable in-depth knowledge in one or more technical disciplines (e.g., cloud, object-oriented programming, full stack development - end to end, quantitative finance, etc.)
  • Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security
  • Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching senior engineers/leads on compliant usage patters and controls
  • Ability to tackle design and functionality problems independently with little to no oversight
  • Must have a strong understanding of end-to-end business processes
  • Enthusiastic to keep learning and growing, in technical aptitude and business understanding
  • Previous software engineering team management experience

Nice to have

  • Software development experience in commodities, finance, or investment banking preferred, or willingness to rapidly learn the business domain
  • Willingness to become proficient and develop in Python if not already a primary language
  • Ability to collaborate with other technology teams to deliver end to end solutions to the business in a constantly changing environment
  • Excellent interpersonal skills to interact confidently and credibly with business users, to understand and agree business requirements and their prioritization

What the JD emphasized

  • Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security
  • Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching senior engineers/leads on compliant usage patters and controls

Other signals

  • AI-assisted engineering practices
  • AI-assisted code review/refactoring
  • AI-assisted development and automation capabilities
  • responsible AI use in engineering workflows
  • validating AI outputs for correctness, performance, and security