Shape the future of financial services at JPMorganChase. Join us to drive innovation, deliver impactful solutions, and lead teams at the forefront of technology.
As Senior Director of Software Engineering at JPMorgan Chase within Operations Technology, you will lead multiple technical domains, managing high-performing teams and collaborating across the organization. You will drive strategic platform development, champion industry best practices, and ensure delivery of scalable, resilient, and user-centric solutions. Your leadership will guide the adoption of advanced technologies and frameworks, aligning with the firm’s vision and objectives.
Job Responsibilities
- Define and execute delivery strategy and roadmap for large-scale, cross-functional engineering programs.
- Lead end-to-end program execution, including planning, resource management, risk mitigation, and stakeholder communication.
- Translate technical vision into actionable plans, partnering with Principal Engineers and Architecture leads.
- Sets and scales multi-department strategy for agentic AI-enabled engineering and SDLC/TLM automation (using enterprise-authorized tools within the work environment) to drive firmwide objectives (speed, scalability, reliability, and cost-to-serve), including portfolio-level standards for AI-orchestrated delivery workflows, release governance, automated test modernization, resilience engineering, and incident response acceleration; establishes guardrails for validation, security, resiliency, traceability, and reuse.
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to drive cross-domain reuse and measurable capacity unlock outcomes across departments.
- Establish and optimize delivery frameworks, governance models, and reporting cadences tailored to program complexity.
- Proactively identify and resolve systemic risks, technical debt, resource gaps, and cross-team dependencies.
- Serve as the primary liaison between Engineering, Product, and Executive leadership, managing program status, trade-offs, and escalations.
- Drive continuous improvement in engineering practices through retrospectives, metrics analysis, and process optimization.
- Leverage AI and approved coding-assist tools to enhance code quality, velocity, and productivity.
- Mentor and develop technical managers and delivery leads, fostering a robust leadership pipeline.
Required qualifications, skills, and capabilities
- Formal training or certification on software engineering concepts and 5+ years applied experience and 15+ years of end-to-end technical program delivery experience, including 5+ years at Director level.
- Proven success delivering complex, multi-team programs at scale and on schedule.
- Deep expertise across the technology stack: API design (REST, SOAP, gRPC, GraphQL), AWS cloud (EKS, networking, serverless, IAM), CI/CD, container orchestration (Kubernetes, Docker), event streaming (Kafka, Kinesis), CDN, front-end frameworks, observability (Datadog, CloudWatch, SLOs/SLIs), large-scale databases (PostgreSQL, Neo4j, Aurora), security, compliance, and QA automation.
- Experience leading multi-organization adoption of agentic AI-enabled engineering operating models (using enterprise-authorized tools within the work environment), including defining governance (human-in-the-loop decisioning, quality gates), measurement frameworks, and secure handling of sensitive inputs/outputs across teams.
- Deep understanding of responsible AI risk, controls, and resiliency/security expectations at scale, with demonstrated ability to advise senior leaders on safe adoption, portfolio governance, and reuse-first strategies.
- Demonstrated experience in AI/ML, Large Language Models (LLM), Agentic AI, and Generative AI, with successful project delivery in these domains.
- Strong ability to assess and challenge architectural designs, both front-end and back-end, and drive sound technical decisions.
- Technical fluency to evaluate architectural trade-offs, service boundaries, cost vs. resilience, and build vs. buy decisions.
- Mastery of modern delivery methodologies (Agile, Scrum, Kanban), with adaptability to context.
Exceptional communication skills, able to translate complex engineering concepts for diverse audiences.
- Hands-on coding experience.
- BS/MS in Computer Science, Engineering, or related technical field.
Preferred qualifications, capabilities, and skills
- Experience working at code level