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.