Lead Software Engineering - Python - Front Office Quant Developer

JPMorgan Chase JPMorgan Chase · Banking · LONDON, LONDON, United Kingdom · Commercial & Investment Bank

Lead Software Engineer for JPMorgan Chase's Equities Front Office Trading and Analytics Team in London. Focuses on developing and enhancing applications for equity derivatives trading, leading the Systematic Quoting Platform workstream, and driving automation using Python and agentic development. The role emphasizes adopting AI-assisted engineering practices for code quality and delivery speed, with a strong focus on responsible AI use and validation.

What you'd actually do

  1. Develop and enhance applications for equity derivatives trading and analytics
  2. Partner with trading desks, technology teams, and Quantitative Research to deliver solutions
  3. Lead the Systematic Quoting Platform workstream for EMEA
  4. Maintain and improve the existing technology stack to ensure stability
  5. Automate Front Office processes and functions using technology solutions

Skills

Required

  • Hands-on experience with systematic trading technology platforms
  • Proven ability to develop, deploy, and maintain commercial service-oriented applications
  • Strong Python skills
  • 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

Nice to have

  • 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

What the JD emphasized

  • agentic development
  • AI-assisted engineering practices
  • responsible AI use