Sr Lead Software Engineer

Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products. 
As a Senior Lead Software Engineer at JPMorganChase within the Commercial & Investment Bank, 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. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications. 
Job responsibilities

• Design and build core application features hands-on (backend, APIs, integration, and UI as needed).
• Own technical design and implementation patterns to deliver secure, scalable, maintainable solutions.
• Lead design/code reviews and enforce engineering standards across the delivery lifecycle.
• Partner with product and UAT teams to translate requirements into working software and support acceptance testing.
• Influence senior business and technology stakeholders; communicate clearly with BAs, PMs, and engineers.
• Drive continuous improvement through pragmatic, innovative solutions, and better team processes.
• Troubleshoot complex issues, prioritize effectively, and deliver to deadlines with a customer-first mindset.
• Mentor engineers and foster a collaborative, inclusive, high-performance team culture.
• Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.

• Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience 
  Strong CS fundamentals: OOAD, data structures/algorithms, and design patterns.
• Expert in Java with modern frameworks (Spring Boot, Dropwizard, or equivalent). Microservices architecture; RESTful services and WebSockets.
• Containers and orchestration: Docker and Kubernetes. Messaging/integration: JMS, RabbitMQ, AMQP, MQ, Kafka.
• Front-end proficiency in at least one modern web framework (React + Redux, Angular, Node.js, etc.). Testing discipline with common frameworks (JUnit, Mockito, Selenium/Cucumber; plus relevant JS test tools).
• Persistence layer experience: JDBC and ORM frameworks (Hibernate/MyBatis). Strong SDLC knowledge and Agile delivery experience.
• Databases: Oracle (strong), Sybase. Cloud experience: AWS/Azure/GCP and/or Cloud Foundry.
• Excellent analytical/debugging skills and strong written/verbal communication. Proven ability to manage stakeholder relationships and prioritize within complex programs
• Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (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 senior engineers/leads on compliant usage patterns and controls.

Preferred qualifications, capabilities, and skills

• Financial services domain experience.
• Technical coach/leader who helps teams solve hard engineering problems.
• Scrum execution experience (planning, backlog grooming, retrospectives).
• Understanding of security standards/frameworks and secure engineering practices.
• Exposure to NoSQL (HBase/Cassandra) and Spark is a plus