Lead Software Engineer UI (React & Python)

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

As a Lead Software Engineer at JPMorganChase within the Commercial & Investment Bank youare 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 are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firms business objectives.

Job responsibilities

• Build and evolve real-time Risk / PnL UI workflows 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 consuming 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 robust error handling and resilience under degraded conditions.
• Implement UI state management and real-time data patterns (streaming updates caching pagination/virtualization) for correctness and performance under high-frequency updates.
• Own end-to-end technical design across UI and services including data contracts schema evolution dependencies and failure modes.
• Drive adoption of enterprise-authorized AI-assisted engineering practices with strong validation standards (secure coding peer review automated testing) and pattern reuse. Drive observability and production excellence: instrumentation monitoring/alerting incident triage root-cause analysis runbooks and reliability improvements.
• Partner with stakeholders to translate business needs into clear requirements and deliver iteratively with strong documentation and communication.
• 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.

Required qualifications capabilities and skills

• Formal training or certification on software engineering concepts and 5 years applied experience.

• Strong front-end engineering experience with Angular and/or React and TypeScript including component design UI testing and maintainability.
• Strong SDLC experience in an enterprise environment: CI/CD automated testing release management and production support with governance/controls.
• Experience building real-time systems (messaging/streaming caching low-latency APIs) and integrating UIs with backend APIs using contract-driven development and safe rollout patterns.
• Proficiency in performance tuning across the stack (services: CPU/memory/IO; UI: responsiveness/render performance) and designing for throughput/backpressure/graceful degradation.
• Experience leading effective use of approved AI-assisted development tools with standards for validating AI outputs (correctness performance security) and responsible AI practices.
• IAM/SSO integration experience (OAuth2/OIDC and/or SAML) JWT/session management and RBAC/entitlements; MFA-aware flows and secure session lifecycle controls
• 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

Preferred qualifications capabilities and skills

• Experience building front-office trading/risk/PnL UIs with strong usability under time pressure.
• Familiarity with real-time UI delivery patterns (e.g. WebSockets/streaming) and ensuring correctness/ordering/user trust.
• Experience with UI operational excellence: client-side telemetry/logging synthetic monitoring performance budgets production troubleshooting.
• Experience leading cross-functional delivery across quant/risk stakeholders production management and multiple engineering teams.