Lead Software Engineer - Java

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible. Join our innovative External Regulatory Financial Control/Strategic Data team at JPMorganChase, where we leverage cutting-edge technology to drive data-driven decision-making and enhance business performance. If you are passionate about transforming data into actionable insights and thrive in a collaborative, high-impact environment, this is the role for you.

As a Lead Software Engineer at JPMorganChase within the External Regulatory Financial Control/Strategic Data team, you will architect and deliver cutting-edge, Java-based applications to process and load critical data across various cloud-based and on-premise data solutions. You will be responsible for developing, testing, and maintaining critical software applications and architectures across multiple technical areas within various business functions in support of the firm's business objectives. You will play a key role in shaping technical direction, mentoring engineers, and driving engineering excellence across the team.

Job responsibilities

• Build and own Spring Boot microservices and REST APIs in Java, from design through production support, delivering high-quality, secure, and well-tested code
• Deliver scalable data-processing services (batch and stream), integrating with messaging and persistence layers to support critical business workflows
• Provide technical leadership across the team by defining architecture direction, guiding design decisions, and ensuring solutions align to External Regulatory Financial Control/Strategic Data outcomes
• Lead architecture and design reviews, document key decisions, and ensure designs meet resiliency, security, and compliance requirements
• Own delivery end-to-end for key initiatives, including scope, technical planning, execution, risk and issue management, and production readiness
• Mentor and coach engineers through pairing, code reviews, and structured feedback to raise overall engineering standards and team effectiveness
• Establish and enforce coding standards, testing strategy, and continuous integration and delivery quality gates to ensure maintainable, secure, production-grade software
• Deploy, monitor, and operate production services on cloud and container platforms, ensuring reliability and observability across environments
• Tackle large-scale engineering challenges using technologies such as Kafka and cloud-native messaging solutions to support high-throughput data pipelines
• 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 advanced applied experience
• Demonstrated experience leading the design and delivery of complex backend systems in a distributed environment, including influencing architecture and technical strategy
• Strong ability to mentor engineers and lead code and design reviews, with a track record of improving engineering quality and delivery practices
• Proficiency in backend development using Java, Spring Boot, and object-oriented programming principles, with hands-on experience in system design, application development, testing, and operational stability
• Experience in large-scale data processing, microservices, API design, Kafka, and observability tools such as Dynatrace, Splunk, and Grafana
• Solid understanding of the Spring Boot ecosystem, including JPA, Spring Security, and Hibernate
• Proficiency in automation, continuous delivery methods, and all aspects of the Software Development Life Cycle
• Solid understanding of Agile delivery practices, with strong continuous integration and delivery, application resiliency, and secure development lifecycle standards
• Working knowledge of SQL and relational databases
• Proven stakeholder management skills, including translating ambiguous requirements into actionable technical plans and communicating trade-offs effectively
• Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security
• Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices

Preferred qualifications, capabilities, and skills

• Familiarity with front-end languages and frameworks such as React and TypeScript
• Solid understanding of containerization using Docker and configuration management utilities such as Helm and Kustomize
• Familiarity with NoSQL databases and their application in distributed system design
• Experience working in regulated financial services environments with exposure to data governance and compliance requirements