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 Consumer & Community Banking - API Marketplace 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.
You will play a pivotal role in designing, building, and enhancing the API Platform that empowers our API developers. We seek engineers with a broad technical perspective and a passion for solving complex challenges using expertise across multiple disciplines. In this role, you will manage end-to-end problem-solving, advocate for effective solutions across diverse technology stacks, and help drive significant business value for our customers through robust API offerings.
Job responsibilities
- Brings discipline and creativity to solve business-critical problems, working with tech leads, product managers, and designers to bring outcomes to fruition
- Identifies opportunities to remove technical debt and works to improve the quality of engineering deliverables
- Communicates with stakeholders and is comfortable leading discussions with customers
- Develops secure and high-quality production code, and reviews and debugs code written by others
- Drives decisions that influence product design, application functionality, technical operations, and processes, providing leadership grounded in technical expertise and effective communication
- Serves as a function-wide subject matter expert in one or more areas of focus
- Contributes to the engineering community as an advocate for firmwide frameworks, tools, and practices of the Software Development Life Cycle
- 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
- Hands-on programming/application development experience utilizing Java, Spring Boot, REST, Microservices, RDBMS and NoSQL databases, Cloud Native, Agile, DevOps, and TDD
- Recent experience with a cloud platform such as AWS, and utilization of container technologies such as Docker and Kubernetes
- Prior experience in building or using API Platforms, with deep expertise in one or more areas of the end-to-end API stack, including cloud connectivity, network diagnosis, resilient systems, API security, authentication/authorization, API gateways, and API design spanning specification, standards, documentation, and governance.
- Advanced knowledge of software applications and technical processes, with considerable in-depth expertise in one or more technical disciplines (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
- Ability to tackle design and functionality problems independently with little to no oversight
- Practical cloud native experience
- Experience in Computer Science, Computer Engineering, Mathematics, or a related technical field
- 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
- Deep understanding of networking and connectivity, including diagnosing network latencies, DNS behavior, cloud connectivity, and content delivery networks
- Strong knowledge of API security, including transport-level security, payload encryption, signature algorithms, certificate management, OAuth, and DDoS protection
- Experience designing highly scalable and resilient software systems on public cloud platforms such as AWS, utilizing various resiliency design principles and practices
- Expertise in API developer specifications, standards, and documentation, with prior experience driving adoption of best practices at scale
- Knowledge or familiarity with modern front-end technologies is a plus
- Knowledge or experience with data engineering, data pipelines, or analytics platform is a plus