If you are a software engineering leader ready to take the reins and drive impact, we’ve got an opportunity just for you.
As a Director of Software Engineering at JPMorganChase within the Digital Technology team, you lead a technical area and drive impact within teams, technologies, and projects across departments. Utilize your in-depth knowledge of software, applications, technical processes, and product management to drive multiple complex projects and initiatives, while serving as a primary decision maker for your teams and be a driver of innovation and solution delivery.
Job Responsibilities
- Leads technology and process implementations to achieve functional technology objectives
- Accountable for decisions that influence teams’ resources, budget, tactical operations, and the execution and implementation of processes and procedures
- Sets direction and governance for agentic AI-enabled engineering and SDLC/TLM automation within a technical area to drive measurable improvements in speed, quality, and operational outcomes (e.g., AI-orchestrated delivery workflows, release readiness controls, automated test modernization, and incident triage acceleration), while establishing guardrails for validation, security, resiliency, traceability, and reuse across teams
- 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 and support capacity unlock initiatives at scale
- Carries governance accountability for coding decisions, control obligations, and measures of success such as cost of ownership, maintainability, and portfolio operations
- Delivers technical solutions that can be leveraged across multiple businesses and domains
- Influences peer leaders and senior stakeholders across the business, product, and technology teams
- Owns the engineering strategy and execution for a Content and Experimentation platform, enabling scalable content delivery, targeting, personalization, and rapid iteration via experimentation
- Partners with Product, Design, Data/Analytics, and Marketing stakeholders to define platform roadmaps, SLAs/SLOs, and measurable outcomes (e.g., experimentation velocity, conversion impact, platform reliability)
- Establishes platform governance for experimentation (guardrails, statistical rigor, auditability, and policy-aligned controls), including standard patterns for feature flags, A/B/n testing, and rollout strategies
- Drives cloud-native delivery on AWS for the platform (e.g., reliability, performance, cost optimization, observability, incident response), with strong focus on secure-by-design and reusable platform capabilities
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 10+ years applied experience. In addition, 5+ years of experience leading technologists to manage, anticipate and solve complex technical items within your domain of expertise
- Experience developing or leading cross-functional teams of technologists
- Experience with hiring, developing, and recognizing talent
- Experience leading adoption of agentic AI-enabled engineering practices (using enterprise-authorized tools within the work environment) across teams, including defining operating expectations (human-in-the-loop validation, quality gates), measuring outcomes, and ensuring secure handling of sensitive inputs/outputs
- Strong understanding of responsible AI use and control expectations in engineering workflows, including data sensitivity, resiliency/security implications, and governance; ability to influence leaders on safe scaling patterns and reuse
- Practical cloud native experience
- Expertise in Computer Science, Computer Engineering, Mathematics, or a related technical field
- Hands-on leadership experience designing and operating content delivery and experimentation capabilities (e.g., feature flags, A/B testing frameworks, rollouts, targeting/personalization) in a multi-team environment
- Strong AWS knowledge for building and running scalable platforms (e.g., networking, compute, storage, security, observability, resiliency patterns, and cost management)
- Experience defining platform operating models (intake, prioritization, self-service enablement, reliability targets, runbooks, and on-call practices) for product-facing engineering platforms
- Strong understanding of API-first and event-driven architectures to integrate content and experimentation services with downstream channels and product applications
Preferred qualifications, capabilities, and skills
- Participate in and lead opportunities with third parties, working to understand why and how we may integrate and leverage their capabilities
- Experience hiring top talent, growing careers, and coaching individuals and managers to higher performance
- Experience operating software platforms
- Strong understanding of AWS services and infrastructure
- Experience with content management platforms (CMS) and content lifecycle concerns (authoring, workflow, governance, localization, versioning, and publishing) to support enterprise-scale content operations