Lead Software Engineer Python full stack

Design and deliver front-office solutions for real-time and end-of-day risk management and profit and loss (PnL) analysis for the Credit Trading team spanning both backend services and UI capabilities.

As a Lead Software Engineer at JPMorgan Chase within the Commercial & Investment Banks Credit Technology team you will join an agile engineering group building secure resilient low-latency platforms that power front-office risk trading and management reporting workflows across Bonds Loans Credit Derivatives and Exotics. You will lead technical delivery across multiple components including real-time services and the web UI layer used by front-office consumers while partnering closely with quant trading risk and production management stakeholders.

Job responsibilities

• Build and evolve real-time and end-of-day Risk / PnL capabilities for credit products including intraday Greeks/sensitivities VaR inputs explain/attribution and scenario/stress runs.
• Design and deliver low-latency high-throughput services that publish risk and PnL to front-office consumers with clear SLAs observability and operational readiness.
• Develop distributed microservices and event-driven pipelines that consume market data trades and reference data; produce risk measures; and serve APIs to UI and downstream systems.
• Lead design and delivery of web UIs for real-time risk/PnL workflows using Angular and/or React with TypeScript including API integration patterns robust error handling and resilient user experiences under degraded conditions.
• Implement UI state management and real-time data patterns (for example streaming updates caching pagination/virtualization) that preserve correctness and performance under high-frequency updates.
• Own end-to-end technical design with awareness of upstream/downstream dependencies data contracts schema evolution and failure modes across both backend services and UI consumers.
• 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. Applies strong engineering rigor: test strategy performance profiling capacity planning resiliency patterns and secure coding across services and UI.
• Drive UI and service observability: instrumentation logs/metrics/tracing where applicable performance monitoring (including client-side performance) and actionable alerting tied to user and system outcomes.
• Deliver production excellence: incident triage root cause analysis runbooks automated recovery and measurable reliability improvements including UI operational readiness and on-call effectiveness.
• Collaborate with stakeholders to translate business needs into clear technical requirements and deliver iteratively with strong documentation and communication.

Required qualifications capabilities and skills

• Formal training or certification on software engineering concepts and 12 years applied experience
• Extensive hands-on experience delivering Python services in production including design development testing troubleshooting and operational support. Strong knowledge of data structures algorithms concurrency and software design principles; ability to lead design discussions and document architecture.
• Demonstrated experience across the full SDLC including CI/CD automated testing release management and production support in a controlled enterprise environment.
• Proven ability to build secure stable maintainable systems in a large enterprise environment with strong controls auditability and SDLC governance.
• Experience building real-time systems including messaging/streaming concepts caching and low-latency APIs.
• Hands-on front-end engineering experience building and operating modern web applications using Angular and/or React and TypeScript with strong proficiency in component design UI testing and maintainability.
• Experience integrating UIs with backend APIs including authentication-aware API access contract-driven development backward compatibility and safe rollout patterns. Proficiency with profiling and performance tuning across the stack (CPU/memory/IO for services; responsiveness and render/interaction performance for UI) designing for throughput backpressure and graceful degradation.
• 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
• Identity and access management experience integrating applications with enterprise IAM/SSO including OAuth2/OIDC and/or SAML JWT/session management and RBAC/entitlements.
• Experience designing and implementing Multi-Factor Authentication (MFA)-aware user flows and secure session lifecycle controls (for example re-authentication token refresh inactivity timeouts) aligned to enterprise security requirements.

Preferred qualifications capabilities and skills

• Experience building UI experiences for trading risk or PnL workflows in a front-office environment with an emphasis on usability under time pressure.
• Familiarity with real-time UI delivery patterns (for example WebSockets or streaming abstractions) and strategies to ensure data correctness ordering and user trust.
• Experience with UI operational excellence practices including client-side logging/telemetry synthetic monitoring performance budgets and production troubleshooting.
• Prior experience leading cross-functional delivery spanning quant/risk stakeholders production management and multiple engineering teams.