Manager, Software Engineering - Developer Experince

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. 6. AI Governance & Risk - Ensure the team follows AI usage guidelines (data handling, code review, IP considerations). - Flag risks from AI-generated code (security, correctness, licensing) proactively. - Maintain visibility into what AI tools the team is using and how they're being used. - Run regular retros and feedback loops on AI-related outcomes. - Review AI-generated outputs alongside the team to build shared quality standards. QUALIFICATIONS: - Experience: 7+ years in software engineering, with 3+ years in a leadership role managing engineering teams. - Technical Expertise: Strong understanding of developer tools, CI/CD pipelines, and modern software development practices. Hands-on experience with AI coding tools (Cursor, Claude Code, Codex, or similar) and an understanding of how to integrate them into engineering workflows. - AI Fluency: Demonstrated ability to operate at the AI Augmented level or above: you personally use AI tools daily and have coached others on effective AI-assisted development. Familiar with prompt engineering, context engineering, and token economics. - Builder Mindset: Comfortable with the 80/20 model (planning and review vs. direct execution). Experience orchestrating work across humans and AI agents, with strong judgment on when to delegate to AI vs. when human decision-making is critical. - Leadership Skills: Proven ability to build and lead high-performing teams. Experience assessing and developing AI fluency across a team. - Problem-Solving: Track record of identifying inefficiencies and implementing scalable solutions, including building or adopting AI-powered tooling and eval frameworks. - Governance Awareness: Understanding of AI & non-AI related risks (security, correctness, licensing, data handling) and experience establishing quality standards for outputs. - Collaboration: Exceptional communication and stakeholder management skills. Ability to translate AI capabilities and limitations to non-technical audiences. - Mindset: Passion for improving developer experiences and driving organizational impact through AI-native practices with a customer first mentality. WHY JOIN US? - Impactful Work: Shape the future of developer productivity at a fast-growing, AI-native SaaS company. - AI-Native Culture: Work in an organization that treats AI as a core competency, not a nice-to-have, with industry-leading investment in AI tooling, agents, and engineering workflows. - Builder Operating Model: Join a team that's redefining how software gets built: orchestrating AI agents, shipping with compound engineering, and measuring what matters. - Growth Opportunities: Advance your care