ClickUp - Manager, Engineering
Requirements
• 6+ years of professional software engineering experience building production software, including substantial time as a hands-on senior engineer, with 2+ years managing an engineering team. • You still code. You're comfortable working in a modern production codebase (TypeScript, Node.js, React, or similar), reviewing PRs with substance, and debugging across the stack. • A track record of delivering customer-facing SaaS products or services, with ownership extending beyond launch to reliability, maintenance, and customer outcomes. • Experience hiring, coaching, and developing engineers, including giving direct feedback, managing performance, and supporting career growth. • Deep technical judgment. You can lead architecture discussions, evaluate trade-offs from first-hand experience, and hold a high engineering bar because you know what good looks like in the code. • Experience partnering closely with product and design to define priorities, scope work, and deliver against clear milestones. • A demonstrated ability to use AI tools and agentic workflows to improve engineering work and reduce manual coordination, with attention to correctness, security, and review. • Comfort working through ambiguity, learning unfamiliar product areas, and making decisions with incomplete information. • Clear communication and effective cross-functional collaboration. You make ownership, trade-offs, risks, and next steps easy to understand. • Daily fluency with AI tools in your own workflow. • Recent, meaningful code contributions as a manager: features, fixes, tooling, or prototypes you shipped yourself. • Experience managing engineers across frontend and backend, or leading delivery across multiple technical disciplines. • Experience building and operating software at scale, including performance, reliability, safe migrations, and incident management. • Experience in a fast-moving product organization, balancing customer-facing delivery with platform improvements and technical debt. • Experience introducing AI-native or agent-driven workflows to an engineering team, with measurable improvements in quality or execution. • Experience building collaboration, productivity, or workflow software, or products used by both individual users and enterprise customers. • Experience leading distributed teams across time zones.
Responsibilities
• Lead and develop a product engineering team. Own hiring, onboarding, mentorship, performance, and career growth, and build a team where expectations are clear and feedback is direct. • Own delivery from planning through release and follow-through. Break work into clear milestones, manage dependencies, surface risks early, and make realistic commitments. • Set priorities with product, design, and engineering leadership. Connect engineering work to customer needs and business outcomes, and make deliberate trade-offs between new features, reliability, and technical debt. • Lead from the front technically. Stay close to the codebase: review PRs, dig into production issues, write code and prototypes when it unblocks the team, and know your systems well enough to spot risk before it ships. • Drive architecture and implementation decisions with your technical leads and senior engineers. Bring real depth to design discussions, challenge assumptions with specifics, and make the call when the team is stuck. • Run an AI-native team. Use AI tools and agentic workflows to improve planning, development, testing, triage, and reporting, while maintaining clear ownership and human review where it matters. • Uphold a high engineering bar across design and code review, automated testing, performance, security, and maintainability. Build quality into delivery rather than treating it as a final checkpoint. • Own the operational health of your team's product area. Establish appropriate monitoring, safe rollout practices, incident response, and on-call ownership, and turn production issues into lasting improvements. • Collaborate across product teams and shared platform teams to resolve dependencies and deliver coherent customer experiences. • Keep priorities, progress, risks, and decisions visible. Use evidence to improve team execution and product outcomes, rather than optimizing for activity counts.
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