Engineering Team Lead-Agentic Surfaces

About monday.com

monday.com is the AI work platform powering the most ambitious teams. 250,000+ customers across departments use us to bring people, workflows, and AI agents together on one flexible platform where AI doesn't just assist, it executes. We move fast, build things that matter, and foster an ownership-driven culture where you're empowered to shape how organizations work and outpace their competition.

About the Group

The Surfaces Group owns monday.com's main work surfaces, the core experience where millions of people plan, track, and run their work every day. That reach puts us where AI meets everyday work: we shape how AI and agents show up where people already work, meeting customers where they are today and taking them where they're going next.

The engineering challenges match the scale: massive datasets in the browser that still feel instant, real-time collaboration across huge accounts, and rendering and data pipelines that keep up with our customers' growth.

About the role

• Lead, grow, and mentor a team of about 5 engineers. The exact scope is open, and we'll shape it around your strengths

• Own core experiences used by millions end to end, from discovery and architecture to delivery and impact after launch

• Take on the hardest technical problems: performance at scale, complex client-side state, and AI quality in production

• Make AI genuinely useful in the flow of work, balancing what customers need now with where the product is going.

• Define how the team works AI-first, including where to move fast and where quality gates apply

• Our stack includes TypeScript, React, Node.js, Ruby on Rails, Redis, MySQL, Kubernetes, and AWS, in a microservices and microfrontends environment

   

Requirements

• 3+ years managing engineering teams, and 6+ years building production-grade web applications.

• A builder at heart: curious about data, product, and UX, and comfortable owning decisions beyond engineering

• A record of shipping user-facing products end to end at scale, with strong technical depth in performance-sensitive, data-heavy products

• AI-first in practice: agentic development tools are part of your daily work, and you've brought these practices to a team before

• Impact-driven: you measure what matters, and you change course when the numbers say so

• Experience shipping GenAI features to production and owning their quality (evals, context engineering, monitoring)- big advantage

• Experience building products from scratch in a startup, or scaling a SaaS product through hypergrowth- advantage

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