When you mentor and advise multiple technical teams and move financial technologies forward, it's a big challenge with big impact. You were made for this.
As a Senior Manager of Software Engineering at JPMorgan Chase within the Consumer and community banking technology team, you serve in a leadership role by providing technical coaching and advisory for multiple technical teams, as well as anticipate the needs and potential dependencies of other functions within the firm. As an expert in your field, your insights influence budget and technical considerations to advance operational efficiencies and functionalities.
Job responsibilities
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5+ years applied experience . In addition, 2 + years of experience leading technologists to manage and solve complex technical items within your domain of expertise
- Strong background infull-stack development:Java/Spring Bootmicroservices andReact or Angular(TypeScript/JavaScript).
- Experience with event-driven architectures and integrations (e.g., Kafka producers/consumers), including retries, idempotency, DLQs, error handling, failure recovery, and operational readiness.
- Experience with cloud and platform technologies (e.g.,AWS and/or Cloud Foundry, containers, CI/CD pipelines).
- Strong engineering fundamentals in automated testing, performance, observability and monitoring tools, and operational stability.
- Demonstrated ability to lead cross-team delivery, manage competing priorities, and drive alignment across stakeholders.
- Strong experience in providing software solutions using SQL and No SQL databases and performance tuning.
Working knowledge of secure engineering practices and designing to meet Cyber Security and Technology Control requirements (e.g., authentication/authorization, secure APIs, data protection, dependency hygiene).
- Experience leading multi-team adoption of enterprise-authorized AI-assisted development and delivery tools, including defining governance/ways of working (human-in-the-loop validation, quality gates), measuring outcomes, and ensuring secure handling of sensitive inputs/outputs.
- Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, resiliency/security implications, and control expectations ability to coach managers/leads and influence leaders on safe scaling patterns.
Practical cloud native experience
Preferred qualifications, capabilities, and skills