Director of Software Engineering - Content and Experimentation

Experteer Overview In this Director role, you will lead a technology area within JPMorganChase's Digital Technology team, driving strategic delivery across departments. You'll steer AI-enabled engineering initiatives, SDLC automation, and scalable content/experimentation platforms to improve speed, quality, and reliability. You collaborate with product, design, data analytics, and marketing to set roadmaps, SLAs/SLOs, and measurable outcomes while guiding governance and secure-by-design practices. This is a chance to shape platform strategy at scale and influence cross-team technical decisions with senior stakeholders. Compensation / Benefits * Lead technology and process implementations to meet functional technology objectives * Make decisions affecting resources, budgets, and operational execution * Set direction and governance for AI-enabled engineering and SDLC automation within a technical area * Apply SDLC toolchain and automation capabilities to improve automation value and scalability * Govern coding decisions, control obligations, and measures of success like cost of ownership and maintainability * Deliver reusable technical solutions across businesses and domains * Influence peer leaders and senior stakeholders across business, product, and technology * Own engineering strategy and execution for a Content and Experimentation platform * Collaborate with Product, Design, Data/Analytics, and Marketing to define roadmaps, SLAs/SLOs, and outcomes * Establish platform governance for experimentation (guardrails, auditing, feature flags, A/B testing, rollout strategies) * Drive cloud-native delivery on AWS focusing on reliability, performance, cost, observability, and incident response Tasks * Formal training or certification on software engineering concepts * 10+ years of applied software engineering experience * 5+ years of experience leading technologists * Experience developing or leading cross-functional teams * Experience with hiring, developing, and recognizing talent * Experience leading adoption of agentic AI-enabled engineering practices across teams * Strong understanding of responsible AI use and governance in engineering workflows * Practical cloud-native experience * Bachelor/Master in Computer Science/Engineering or related field (implied by expertise) * Hands-on leadership in content delivery and experimentation capabilities in a multi-team environment * Strong AWS knowledge for scalable platforms * Experience defining platform operating models for product-facing engineering platforms * Strong understanding of API-first and event-driven architectures Key requirements *

influence * Govern coding decisions, control obligations, and measures of success like cost of ownership and maintainability * Deliver reusable technical solutions across businesses and domains * Influence peer leaders and senior stakeholders across business, product, and technology * Own engineering strategy and execution for a Content and Experimentation platform * Collaborate with Product, Design, Data/Analytics, and Marketing to define roadmaps, SLAs/SLOs, and outcomes * Establish platform governance for experimentation (guardrails, auditing, feature flags, A/B testing, rollout strategies) * Drive cloud-native delivery on AWS focusing on reliability, performance, cost, observability, and incident response Tasks * Formal training or certification on software engineering concepts * 10+ years of applied software engineering experience * 5+ years of experience leading technologists * Experience developing or leading cross-functional teams * Experience with hiring, developing, and aaaaaa years talent * Experience leading adoption of agentic AI-enabled engineering practices across teams * Strong understanding of responsible AI use and governance in engineering workflows * Practical cloud-native experience * Bachelor/Master in Computer Science/Engineering or related field (implied by expertise) * Hands-on leadership in content delivery and experimentation capabilities in a multi-team environment * Strong AWS knowledge for scalable platforms * Experience defining platform operating models for product-facing engineering platforms * Strong understanding of API-first and event-driven architectures Key requirements *