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Salary
≈ $134k – $272k per year (Estimated)
Location
In office (London)
Seniority
Staff

Confirmed on the employer's own hiring board on Oct 21, 2026. First seen by Alion on Jul 20, 2026. JPMorganChase scores A on the Alion truth index.

Overview
Company
Impact
Profile match
JPMorganChase is the largest bank in the United States by assets and one of the most systemically important financial institutions in the world, with a lineage running back through more than a thousand predecessor firms to the 1799 founding of the Bank of the Manhattan Company. It combines a dominant investment bank and markets business with Chase, the largest retail banking franchise in America, plus commercial banking and asset and wealth management. Headquartered in New York, the group is unusual among banks for the scale of its technology spending, running one of the largest engineering organisations of any financial institution and deploying its own internal AI platform across the firm.

Join us to shape the future of equity derivatives trading through technology. You’ll partner closely with trading desks, technology teams, and Quantitative Research to deliver impactful solutions. We offer a dynamic environment where you can propose and explore new ideas, automate processes, and collaborate globally. Your work will directly influence business transformation and provide opportunities for career growth. Be part of an agile, delivery-focused team that values creativity and excellence.

As a Lead Software Engineer in the Equities Front Office Trading and Analytics Team, you will lead the Systematic Quoting Platform workstream for EMEA. You will develop and enhance applications critical to the business, working closely with trading, sales, and Quantitative Research teams. Your expertise in Python and agentic development will drive automation and innovation. You will contribute to a global platform, ensuring stability and delivering high-quality solutions. This role offers the chance to make a meaningful impact in a fast-paced, collaborative environment.

Job Responsibilities:

  • Develop and enhance applications for equity derivatives trading and analytics
  • Partner with trading desks, technology teams, and Quantitative Research to deliver solutions
  • Lead the Systematic Quoting Platform workstream for EMEA
  • Maintain and improve the existing technology stack to ensure stability
  • Automate Front Office processes and functions using technology solutions
  • Collaborate with global and local counterparts to solve business problems
  • Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
  • 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.
  • Participate in business transformation projects across analytics, marking, and publishing
  • Propose and explore new solutions to drive competitive advantage
  • Apply disciplined code management, testing, and deployment practices

Required Qualifications, Capabilities, and Skills:

  • Hands-on experience with systematic trading technology platforms
  • Proven ability to develop, deploy, and maintain commercial service-oriented applications
  • Strong Python skills and familiarity with agentic development (ADLC)
  • Business knowledge of simple derivative products (vanilla options, variance swaps, strategies involving vanillas)
  • Understanding of pricing and risk evaluation using Greeks
  • Experience with at least one modern programming language (Python, Java, etc.)
  • Knowledge of at least one relational database (Sybase, SQL Server, Oracle, etc.)
  • Demonstrated experience leading effective use of approved AI-assisted software development tools (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 engineers on safe, compliant adoption within delivery practices
  • Effective utilization of unit testing
  • Experience across the full project lifecycle

Preferred Qualifications, Capabilities, and Skills:

  • Equities business knowledge or relevant experience in other business areas. Unix or Linux knowledge
  • Working knowledge of continuous integration and deployment processes
  • Experience with project management
  • Familiarity with service-oriented platforms and current generation open source frameworks
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