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ClickUp is hiring a Manager of Software Engineering focused on Developer Experience to lead a high-impact team improving developer workflows and reducing friction across the engineering organization. You will oversee CI/CD pipelines, build systems, and internal tools—including AI-powered tooling and agents—while ensuring infrastructure is scalable, reliable, and secure. You'll evaluate and implement new AI-native technologies, balancing token economics, compute costs, and AI spend against productivity gains.
As a people leader, you'll build, mentor, and lead a team of engineers dedicated to developer productivity. You'll foster collaboration and innovation, set clear goals, and provide regular feedback. A key responsibility is assessing and developing AI fluency across your team (Assisted, Augmented, Native levels), coaching engineers on effective AI-assisted development, and creating space for AI experimentation through dedicated time and safe-to-fail projects.
You'll collaborate closely with engineering, product, and design teams to align priorities and advocate for developer needs. You'll define and track metrics on developer productivity, satisfaction, and AI-driven gains, using data-driven insights to prioritize initiatives. You'll identify and eliminate pain points in the development lifecycle, drive adoption of AI coding tools (Cursor, Claude Code, Copilots) as defaults, and ensure every team member has access and is actively using AI tools.
You'll also establish AI governance and risk practices: ensuring the team follows AI usage guidelines, flagging risks from AI-generated code (security, correctness, licensing), maintaining visibility into AI tool usage, and building shared quality standards through regular retros and feedback loops.
QUALIFICATIONS:
- 7+ years in software engineering, with 3+ years in a leadership role managing engineering teams
- 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 ability to integrate them into engineering workflows
- Demonstrated AI fluency at Augmented level or above: daily personal use of AI tools and experience coaching others on effective AI-assisted development
- Familiarity with prompt engineering, context engineering, and token economics
- Comfortable with the 80/20 model (planning and review vs. direct execution); experience orchestrating work across humans and AI agents
- Proven ability to build and lead high-performing teams with experience assessing and developing AI fluency
- Track record of identifying inefficiencies and implementing scalable solutions, including building or adopting AI-powered tooling
- Understanding of AI and non-AI related risks (security, correctness, licensing, data handling) and experience establishing quality standards
- Exceptional communication and stakeholder management skills; ability to translate AI capabilities and limitations to non-technical audiences
- Passion for improving developer experiences and driving organizational impact through AI-native practices
