Director of Software Engineering - Digital Markets Execution Technology - Executive Director (Hiring Immediately)

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 Corporate & Investment Bank, Markets, Digital Markets Execution Technology (DMET) – Execute platform, you will 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. Execute is JPMorganChase’s award-winning, industry-leading single-dealer platform, recognised in 2025 and 2026 for best trading platform, best execution, best FX platform, and FX data and analytics. In this role you will be the senior technical leader for Line of Business delivery across the Execute platform, supporting both our internal Sales and Trading users and JPMorgan’s external clients. You will set the architecture and engineering direction, own the quality, performance and resiliency of what ships, and be accountable for the technical decisions, standards and controls across your teams, while growing the engineers and engineering leaders who deliver it. You will join a growing, co-located, senior and high-agency engineering team in London, building on deep pedigree in enterprise-scale integration, aggregating many Line of Business services into a single platform, alongside large-scale UI engineering, and an industry-leading position in agentic development practices. You will stay close to the code and the design, shaping the next generation of Sales Execution tooling and setting the technical bar for how it is built. 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 Leads Line of Business delivery across the Execute platform, owning roadmap, prioritisation and outcomes for capabilities serving internal Sales and Trading users and external JPMorgan clients Accountable for the production stability, resiliency and client experience of a latency-sensitive, client-facing trading platform, including operational readiness and post-incident improvement Required qualifications, skills, and capabilities Formal training or certification on software engineering concepts and expert applied experience. In addition, 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 Experience leading delivery of client-facing, high-performance platforms, ideally in trading, pricing or capital markets, balancing the needs of internal users and external clients Experience leading enterprise-scale integration and aggregation of multiple services or business domains into a single platform, with the technical depth to guide API, data and UI architecture across it Expertise in Computer Science, Computer Engineering, Mathematics, or a related technical field