Manager, Software Engineering - Developer Experience

About the role

At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀

ROLE OVERVIEW

As the Engineering Manager - Developer Productivity, you will lead a high-impact team focused on improving developer workflows, reducing friction, and enhancing the overall engineering experience. You’ll collaborate across teams to identify bottlenecks, implement scalable solutions, and foster a culture of continuous improvement. Your work will directly influence the speed, quality, and happiness of our engineering organization.

RESPONSIBILITIES:

1. Infrastructure & Tooling - Oversee the development and maintenance of CI/CD pipelines, build systems, and internal tools, including AI-powered internal tooling and agents. - Ensure our developer infrastructure is scalable, reliable, and secure. - Evaluate and implement new AI-native technologies, considering token economics, compute costs, and AI spend alongside productivity gains.

2. Team Leadership & AI People Development - Build, mentor, and lead a team of engineers focused on developer productivity. - Foster a culture of collaboration, innovation, and accountability. - Set clear goals and provide regular feedback to drive team performance in partnership with your Director. - Assess each report's AI fluency level (Assisted, Augmented, Native) and set individual growth targets. - Include AI fluency as a coaching topic in 1:1s; pair less AI-fluent engineers with AI-native peers for knowledge transfer. - Create space for AI experimentation: dedicated time, safe-to-fail projects, and learning sprints. - Recognize and reward AI-driven improvements in performance conversations.

3. Collaboration & Communication - Work closely with engineering, product, and design teams to align priorities. - Advocate for developer needs and ensure alignment with company goals. - Communicate capabilities and limitations to non-technical stakeholders. - Write specs, rules files, and documentation that make AI more effective for the whole team.

4. Metrics & Continuous Improvement - Define and track key metrics to measure developer productivity, satisfaction, and AI-driven productivity gains. - Use data-driven insights to prioritize initiatives and demonstrate impact. - Track team-level AI adoption metrics and report on AI-augmented workflow effectiveness. - Continuously iterate on processes to improve engineering velocity and quality.

5. AI-Native Developer Experience - Identify and eliminate pain points in the development lifecycle, with a focus on AI-augmented workflows. - Drive adoption of AI coding tools (Cursor, Brain, copilots) as the default across engineering teams. - Ensure every team member has access to and is actively using AI tools; track adoption and remove blockers (tooling, access, training). - Partner with engineering teams to design AI-augmented development workflows that multiply team velocity. - Coach engineers on the Builder model: planning, delegating to agents, reviewing with judgment, and shipping with velocity.