Sr Lead Software Engineer- Lending

Out of the successful launch of Chase in 2021, we’re a new team, with a new mission. We’re creating products that solve real world problems and put customers at the center - all in an environment that nurtures skills and helps you realize your potential. Our team is key to our success. We’re people-first. We value collaboration, curiosity and commitment.

As a Lead Software Engineer at JPMorgan Chase within the Accelerator business, you are the heart of this venture, focused on getting smart ideas into the hands of our customers. You have a curious mindset, thrive in collaborative squads, and are passionate about new technology. By your nature, you are also solution-oriented, commercially savvy and have a head for fintech. You thrive in working in tribes and squads that focus on specific products and projects – and depending on your strengths and interests, you'll have the opportunity to move between them.

While we’re looking for professional skills, culture is just as important to us. We understand that everyone's unique – and that diversity of thought, experience and background is what makes a good team, great. By bringing people with different points of view together, we can represent everyone and truly reflect the communities we serve. This way, there's scope for you to make a huge difference – on us as a company, and on our clients and business partners around the world.

Job Responsibilities

• Identify problems, propose solutions, and contribute to solving issues beyond your specialty.

• Use domain modeling techniques to build best-in-class business products.

• Structure software for easy understanding, testing, and evolution.

• Build scalable solutions that avoid single points of failure and continuously update technologies and patterns.

• Develop secure code to protect customers and the organization from malicious actors.

• Investigate and fix issues promptly, ensuring zero downtime for end-users during releases.

• Monitor performance and use the right approach to identify and solve problems.

Required qualifications, capabilities and skills

• Formal training or certification in software engineering concepts and 5+ years of applied experience.

• Experience as a back-end software engineer with a solid approach to writing unit-level tests using mocking frameworks and automating component, integration, and end-to-end tests.

• Extensive experience with JVM languages (Java/Scala/Kotlin, preferably Java 8+) and automating deployment, releases, and testing in CI/CD pipelines.

• Understanding of security frameworks/standards, data streaming and messaging frameworks (Kafka, Spark, etc.), distributed tracing and monitoring (Zipkin, OpenTracing, Prometheus, ELK stack, Micrometer metrics, etc.), and experience with containers (Docker, Kubernetes, etc.).

• Professional experience in an agile, dynamic, and customer-facing environment.

• Understanding of distributed systems and cloud technologies (AWS, GCP, Azure, etc.), dependency injection frameworks (Spring/SpringBoot, Guice, etc.), microservices architecture, RESTful APIs, web technologies, and relational databases.

• 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.

Preferred qualifications, capabilities and skills

• Ability to work in a collaborative environment and coach team members on coding practices, design principles, and implementation patterns for high-quality maintainable solutions.

• Ability to work in a dynamic, agile environment within a geographically distributed team and focus on promptly addressing customer needs.

• Work within a diverse and inclusive team.

• Technically curious, versatile, and solution-oriented.

• 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