salmon-group - Head of Engineering Productivity
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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.
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.
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