Sr. Director of Software Engineering

JPMorganChase•Wilmington, NC

About The Position

As a Senior Director of Software Engineering at JPMorgan Chase within Consumer & Community Banking Operations Technology, you will lead multiple technical domains, manage high-performing teams, and collaborate across the organization. You will drive strategic platform development, champion industry best practices, and ensure delivery of scalable, resilient, user-centric solutions. Your leadership will guide the adoption of advanced technologies and frameworks, aligning with the firm’s vision and objectives. The role sets and scales multi-department strategy for agentic AI-enabled engineering and SDLC/TLM automation using enterprise-authorized tools within the work environment. It establishes portfolio-level standards and guardrails for AI-orchestrated delivery workflows, release governance, automated test modernization, resilience engineering, incident response acceleration, validation, security, traceability, and reuse. The position applies software development life cycle toolchain knowledge to drive cross-domain reuse and measurable capacity gains across departments.

Requirements

Formal training or certification in software engineering concepts and 10+ years of applied experience.
5+ years of experience leading technologists to manage, anticipate, and solve complex technical issues within an area of expertise.
Proven success delivering complex, multi-team programs at scale and on schedule.
Experience developing or leading large or cross-functional teams of technologists.
Deep expertise across the technology stack, including API design (REST, SOAP, gRPC, GraphQL); AWS cloud (EKS, networking, serverless, IAM); CI/CD; Kubernetes and Docker; Kafka and 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, including defining governance, human-in-the-loop decisioning, quality gates, measurement frameworks, and secure handling of sensitive inputs and outputs across teams.
Deep understanding of responsible AI risk, controls, and resiliency and security expectations at scale, with the ability to advise senior leaders on safe adoption, portfolio governance, and reuse-first strategies.
Experience leading complex projects supporting system design, testing, and operational stability.
Experience with hiring, developing, and recognizing talent.
Mastery of modern delivery methodologies such as Agile, Scrum, and Kanban, with adaptability to context.
Hands-on coding experience.
Extensive practical cloud-native experience.

Nice To Haves

Demonstrated prior experience influencing across highly matrixed, complex organizations and delivering value at scale.
BS/MS in Computer Science, Engineering, or a related technical field.

Responsibilities

Lead multiple technology and process implementations across departments to achieve firmwide technology objectives.
Directly manage multiple areas with a strategic transactional focus.
Set and scale multi-department strategy for agentic AI-enabled engineering and SDLC/TLM automation to advance speed, scalability, reliability, and cost-to-serve objectives.
Establish portfolio-level standards and guardrails for AI-orchestrated delivery workflows, release governance, automated test modernization, resilience engineering, incident response acceleration, validation, security, resiliency, traceability, and reuse.
Apply knowledge of 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.
Provide leadership and high-level direction to teams, frequently overseeing employee populations across multiple platforms, divisions, and lines of business.
Act as the primary interface with senior leaders, stakeholders, and executives, driving consensus across competing objectives.
Manage multiple stakeholders, complex projects, and large cross-product collaborations.
Influence peer leaders and senior stakeholders across business, product, and technology teams.
Lead complex projects supporting system design, testing, and operational stability.
Hire, develop, and recognize talent.