We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.
As a Lead Software Engineer at JPMorganChase within the Infrastructure Platforms, Data Center Services team, you are 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. You will take ownership of technical delivery end-to-end while actively engaging with stakeholders to translate business needs into well-planned, high-quality software solutions. This role demands a self-starter who thrives in a collaborative environment, can manage competing priorities, and drives engineering excellence across the team.
Job responsibilities
- Design, develop, and deliver full stack software solutions across frontend (React) and backend (Node.js/TypeScript, Python) services, applying strong problem-solving skills to break down complex technical challenges.
- Engage directly with stakeholders and product owners to gather requirements, clarify scope, and ensure technical solutions align with business objectives.
- Lead development planning activities including backlog refinement, sprint planning, effort estimation, and technical roadmap definition, ensuring the team delivers incrementally and predictably.
- 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.
- Develop secure, high-quality production code and review peers' work to maintain consistency, reliability, and adherence to engineering standards.
- Identify opportunities to eliminate or automate remediation of recurring issues to improve the overall operational stability of applications and systems.
- Maintain clear and organised documentation including technical designs, architecture decisions, and runbooks, ensuring knowledge is shared and accessible.
- Leverage AI-assisted development tools (e.g., GitHub Copilot, AI code review assistants) to improve productivity, code quality, and delivery speed, and champion their effective adoption within the team.
- Participate in communities of practice across Software Engineering to drive awareness and adoption of modern tooling, patterns, and best practices.
- Mentor and support junior engineers
Required qualifications, capabilities, and skills
- Bachelor’s Degree in Computer Science, Cybersecurity, Data Science, or related disciplines
- Formal training or certification in software engineering concepts and 5+ years of applied experience delivering production software.
- Hands-on practical experience across the full Software Development Life Cycle, including system design, application development, testing, CI/CD pipelines, and operational support.
- Strong proficiency in frontend development with React (including state management and testing with Jest/React Testing Library).
- Advanced knowledge in backend development using Node.js and TypeScript to build RESTful APIs, along with strong experience in writing and maintaining comprehensive unit, functional, and integration tests.
- Demonstrated ability to communicate effectively with technical and non-technical stakeholders, translating business requirements into actionable technical plans.
- Experience working collaboratively in agile teams and participating in Scrum ceremonies (stand-ups, retrospectives, sprint planning); experience facilitating or running ceremonies.
- 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
- Experience with databases such as MySQL or similar, along with exposure to cloud platforms and infrastructure-as-code practices, and familiarity with API documentation standards such as OpenAPI/Swagger.
Preferred qualifications, capabilities, and skills
- Experience with other modern frontend frameworks (e.g., Angular). Experience with Python for backend services or tooling.
- Proficiency with design and prototyping tools such as Figma for collaborating on UI/UX requirements is highly desirable.
- Experience with traditional AI/ML, such as predictive analysis, is highly desirable.