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