Head of Engineering Productivity

We are looking for a Head of Engineering Productivity

Responsibilities

• Study how different roles actually work: interview people, observe workflows, map jobs-to-be-done, dependencies, and process breakdowns.

• Build and maintain a structured library of recurring tasks and subtasks across roles, with recommended tools, workflows, and best practices.

• Identify bottlenecks, handoffs, wait states, and rework across the SDLC and redesign workflows to improve speed and quality.

• Evaluate where AI-assisted and tool-assisted workflows can materially improve output quality, cycle time, and effort.

• Design and implement standard internal tooling, guides, and operating practices for modern software development, including agentic and vibe-coding workflows where useful.

• Define safe and practical standards for taking AI-assisted or vibe-coded applications to production, including review, testing, security, and sign-off requirements.

• Partner with Engineering, Product, QA, Data, Architecture, Security, and DevOps leaders to improve end-to-end software delivery. Drive adoption of improved workflows through training, documentation, support, and close partnership with teams.

• Build internal knowledge systems that make code, documentation, configurations, and operational knowledge easier to access and use in day-to-day work.

• Run pilots and experiments to validate new productivity approaches, measure impact, and scale successful practices.

Requirements

• 5+ years of experience in software engineering, developer productivity, engineering management, or a closely related role.

• Strong hands-on background in software development and engineering workflows; able to go deep into tools, systems, and day-to-day execution.

• Proven understanding of the full SDLC, including planning, development, testing, release, operations, and cross-functional delivery processes.

• Solid experience improving developer productivity, engineering effectiveness, or software delivery processes at team or org level.

• Strong understanding of how engineering, QA, analysts, product managers, and engineering managers work together in practice.

• Up-to-date knowledge of modern developer tools and platforms, such as Git, GitLab, Jira, Confluence, Gradle, CI/CD systems, Kubernetes, IDEs, internal developer platforms, and developer environment tooling.

• Good understanding of DevOps practices, release processes, environment management, observability, and production readiness.

• Strong analytical skills; able to break work into tasks and dependencies, identify bottlenecks, and redesign workflows for higher speed and quality.

• Experience running structured experiments or pilots, measuring impact, and scaling successful practices.

• Practical understanding of modern AI-assisted development tools and agentic workflows, with the ability to judge where they help and where they do not.

• Strong communication skills; able to interview teams, understand real working patterns, and turn findings into practical improvements.

• Strong ownership and execution skills; able to independently drive ambiguous, cross-functional initiatives from idea to adoption.

• Experience leading small teams, coordinating cross-functional efforts, or influencing senior stakeholders is a plus.

• Background in fintech, regulated environments, or secure software delivery is a plus.