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.
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.
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.
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.
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 career on a clear AI-native career pathway with structured fluency levels and development support.
Flexible Environment: Enjoy the freedom of remote work with a global team.
Equal Opportunity Employer
ClickUp is an Equal Opportunity Employer, and qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin.
Privacy Notice
ClickUp collects and processes personal data in accordance with applicable data protection laws. You can find further details by viewing our Global Candidate Privacy Notice.
If you are a Philippine Job Applicant, please also see our Philippine Data Privacy Notice for further details.
Visa Sponsorship
Please note we are unable to sponsor or take over sponsorship of an employment visa for roles outside of engineering and product at this time. Sponsorship for engineering and product roles is not guaranteed, but is instead based on the business needs for that specific role at that time. Please reach out to the recruiter with any questions.
Fraud Alert
ClickUp Talent Acquisition will only initiate contact via an @clickup.com email or through our official careers portal on clickup.com. We will never request fees, payments, or sensitive personal information. Please disregard any offers received outside these channels and report them to support@clickup.com.
AI Processing Notice
ClickUp may use artificial intelligence and machine learning technologies to help review and screen candidates’ employment applications against role-related criteria. These tools support, but do not replace, human decision‑making. If you have questions or need an accommodation in the recruitment process, please contact us at AskPeople@ClickUp.com.
