oracle
Senior Lead Software Engineer - Full Stack
JPMorgan Chase
Jersey City, USA
Full-time
Senior · 5+ years experience
Onsite
Discovered 3 days ago
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Key Skills for This Role
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Job responsibilities
- Set the technical direction and architecture for the ALMonD web platform across the front end, service layer, and integration with the simulation engine, with a focus on scalability, performance, and long-term maintainability.
- Build and maintain full-stack features end to end, from React/TypeScript user interfaces through Python services and APIs, with Java services where needed, deployed on AWS.
- Design intuitive workflows for configuring, running, and comparing interest rate simulations and scenarios, partnering with Treasury, CIO, and risk stakeholders to translate quantitative requirements into usable product features.
- Develop high-performance data visualizations, grids, and dashboards that render large simulation result sets (e.g., NII and EVE sensitivities, scenario comparisons, time series) with speed, clarity, and accuracy.
- Lead the team's adoption of AI-assisted engineering practices using enterprise-authorized tools (e.g., for coding, refactoring, test generation, code review, and troubleshooting), and set clear standards for validating AI outputs for correctness, performance, and security.
- Identify and prototype opportunities to bring AI into the product and engineering workflow, such as natural language scenario setup, AI-generated explanations of simulation results, and automation of repetitive development and operational tasks.
- Set and enforce engineering standards for accessibility, performance, security-by-design, and automated testing (unit, integration, and end-to-end).
- Write secure, high-quality production code and comprehensive tests, and contribute actively to code reviews as author and reviewer with a focus on maintainability, clarity, and consistency.
- Build observability into front-end and back-end services (logs, metrics, tracing, real-user monitoring), troubleshoot production issues, take part in incident response as needed, and automate fixes for recurring problems.
- Act as a technical mentor and multiplier for the team through design reviews, pairing, and hands-on guidance, influencing engineering direction without formal people management.
- Collaborate with Product, Treasury, CIO, Risk, and Quantitative teams to refine requirements, break down work, and deliver iteratively across Agile increments.
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5+ years applied experience.
- Advanced Python proficiency, including building production services and APIs, type hints, packaging, testing, and performance tuning.
- Working experience with Java services, with the ability to contribute to and review Java code alongside Python.
- Advanced proficiency in React and TypeScript/JavaScript, including modern state management, component-based architecture, and front-end performance optimization.
- Strong hands-on system design and full-stack application development skills, with demonstrated production ownership (delivery, stability, incident response, and continuous improvement).
- Experience building data-heavy user interfaces, including large interactive grids, charts, and dashboards.
- Proven experience building authenticated API integrations (REST and streaming/WebSocket), including SSO, pagination, retry/backoff, and robust error handling.
- Hands-on experience building and deploying applications on AWS, along with modern CI/CD practices, including automated testing, linting, type checking, and a disciplined git/PR workflow.
- Demonstrated experience using enterprise-authorized AI-assisted development tools in day-to-day engineering, with the ability to set team expectations for using them responsibly and validating their outputs.
- Strong understanding of web security, accessibility (WCAG), and front-end performance best practices.
- Proven track record of technical leadership, including driving architecture decisions, mentoring engineers, and influencing across teams without direct authority.
Preferred qualifications, capabilities, and skills
- Preferred financial services, especially Treasury, asset liability management (ALM), interest rate risk, fixed income, or balance sheet analytics.
- Exposure in building user interfaces for simulation, modeling, or analytics platforms with long-running computations.
- Hands-on experience building generative AI/LLM features into products, such as retrieval-augmented generation (RAG), tool/function calling, or agent workflows.
- Familiarity with emerging AI standards and patterns such as MCP (Model Context Protocol) and agent skills.
- Familiarity with micro-frontend architectures, design systems, or shared UI component libraries.
- Exposure to distributed computing or cloud data platforms on AWS.
- Familiarity in building in regulated environments with strong audit, access control, and change management requirements.
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