Director of Software Engineering - Content and Experimentation (Digital)

Director of Software EngineeringIf 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 ResponsibilitiesLeads technology and process implementations to achieve functional technology objectivesAccountable for decisions that influence teams' resources, budget, tactical operations, and the execution and implementation of processes and proceduresSets 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 teamsApplies 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 scaleCarries governance accountability for coding decisions, control obligations, and measures of success such as cost of ownership, maintainability, and portfolio operationsDelivers technical solutions that can be leveraged across multiple businesses and domainsInfluences peer leaders and senior stakeholders across the business, product, and technology teamsOwns the engineering strategy and execution for a Content and Experimentation platform, enabling scalable content delivery, targeting, personalization, and rapid iteration via experimentationPartners 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 strategiesDrives 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 capabilitiesRequired qualifications, capabilities, and skillsFormal 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 expertiseExperience developing or leading cross-functional teams of technologistsExperience with hiring, developing, and recognizing talentExperience 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/outputsStrong 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 reusePractical cloud native experienceExpertise in Computer Science, Computer Engineering, Mathematics, or a related technical fieldHands-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 environmentStrong 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 platformsStrong understanding of API-first and event-driven architectures to integrate content and experimentation services with downstream channels and product applicationsPreferred qualifications, capabilities, and skillsParticipate in and lead opportunities with third parties, working to understand why and how we may integrate and leverage their capabilitiesExperience hiring top talent, growing careers, and coaching individuals and managers to higher performanceExperience operating software platformsStrong understanding of AWS services and infrastructureExperience with content management platforms (CMS) and content lifecycle concerns (authoring, workflow, governance, localization, versioning, and publishing) to support enterprise-scale content operations