Lead Software Engineer-Full-stack

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 JPMorgan Chase within the Infrastructure Platforms 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. 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 firm's business objectives.

Job responsibilities

• Design, develop, and deliver end-to-end full-stack solutions (UI, backend services/APIs, and database scripts), applying creative problem-solving beyond routine approaches.
• Build scalable, resilient applications using modern technologies and frameworks; develop and integrate RESTful APIs, microservices, and backend services; create responsive UI components (e.g., React, Angular).
• Create secure, high-quality production code, maintaining reliable algorithms and integrations with appropriate systems.
• Lead requirements clarification and delivery readiness by partnering with stakeholders and product leads to translate objectives into actionable epics/stories with clear acceptance criteria and definition of done.
• Facilitate effective stakeholder engagement through customer/user discussions, working sessions, and reviews; drive agendas, capture decisions, and ensure follow-through on actions.
• Maintain a high-quality delivery backlog by supporting product backlog refinement (decomposition, prioritization, sequencing), ensuring alignment to customer/business value.
• Proactively identify and communicate risks, dependencies, and trade-offs, proposing mitigation options to avoid timeline surprises.
• Leverage AI-assisted development tools and techniques to accelerate development/refactoring, improve code quality, and automate testing, documentation, and debugging.
• Participate in design/code reviews and agile ceremonies; optimize performance, scalability, and reliability; ensure adherence to secure coding, risk and control standards; contribute to automation, reusable components, platform engineering standards, and engineering communities—while fostering a culture of diversity, inclusion, and respect.
• 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
• Hands-on practical experience delivering system design, application development, testing, and operational stability.
• Advanced proficiency in one or more modern programming languages, with experience developing, debugging, and maintaining code in a large corporate environment.
• Full-stack SDLC experience across backend technologies (Java, Spring Boot, Python).
• Frontend development experience using JavaScript, HTML5, CSS3, and modern frameworks such as React and/or Angular.
• Database experience with Oracle and/or MS SQL Server, including database querying languages.
• Reporting and visualization experience using Tableau (or similar tools).
• Proficiency in automation and continuous delivery methods, including unit, functional, and regression testing, and CI/CD practices.
• Solid understanding of agile methodologies, application resiliency, and secure engineering practices.
• Practical cloud-native experience, plus demonstrated proficiency in technical disciplines (e.g., cloud, AI/ML/mobile), including AI-driven/GenAI tools for code generation, optimization, testing, and documentation, and in-depth knowledge of financial services and related IT systems.
• 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