Software Engineer Tech Lead – AI Workflows & Automations

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 team

AI Workflows & Automations is the team building monday.com 's engine for turning intent into action — the layer that lets both our customers and our own R&D organization describe an outcome and have AI agents plan, execute, and verify the work. We own the automation and workflow infrastructure that powers AI-driven execution across the platform: from the building blocks that let agents trigger, sequence, and monitor multi-step processes, to the frameworks that make those processes reliable, observable, and safe to run autonomously at scale.

We sit at the intersection of product and internal developer experience: the same primitives we build for customer-facing AI workflows also shape how monday.com engineers themselves use AI to plan, build, test, and ship. We're a small, senior team that moves fast, cares deeply about simplicity, and treats AI not as a bolt-on feature but as a first-class way of working.

About the role

As Tech Lead, you'll set the technical direction for how AI Workflows & Automations builds — and how it uses AI to build better and faster. This is a hands-on role: you'll be writing code, reviewing architecture, and in the weeds with the team day to day, while also owning the strategy for how AI-assisted development gets adopted, measured, and improved across the group.

Lead the design and delivery of core workflow and automation infrastructure, from architecture through production, while staying hands-on in the codebase.

Champion and operationalize AI-assisted development across the team — from AI-native coding workflows and agent-driven PR review to automated testing, spec generation, and release processes.

Define and evolve the team's engineering strategy for leveraging AI throughout the SDLC: identify where AI tooling genuinely speeds up delivery versus where it adds noise, and make the call.

Drive process improvements that compound — tightening feedback loops, reducing manual toil, and raising the bar on quality without adding ceremony.

Mentor engineers on both the craft of software engineering and the emerging craft of working effectively alongside AI agents and copilots.

Partner closely with product, design, and adjacent R&D teams to translate ambiguous problems into clear technical plans.

Own technical decision-making for the team: architecture tradeoffs, build-vs-buy calls on AI tooling, and when to invest in platform work versus feature velocity.

Our stack: Node.js, TypeScript, React, AWS, Kubernetes, Redis, MySQL, Elasticsearch, and a growing set of in-house and third-party AI agent frameworks.

Requirements

7+ years of professional software engineering experience, including full-stack application development end-to-end.

2+ years in a tech lead, staff, or similar role owning technical direction for a team, not just a feature.

Hands-on experience using AI tools (copilots, agentic coding tools, LLM-based automation) to meaningfully speed up real engineering work — not just experimentation.

Strong system design and architecture skills, with the judgment to know when simple beats clever.

Track record of driving process or workflow improvements that measurably improved a team's velocity or quality.

Experience building workflow, automation, or orchestration systems is a strong plus.

Excellent communication skills — able to turn ambiguity into a plan and bring a team along with you.

Team player, low-ego, strong sense of ownership, comfortable both coding and setting direction.

DevOps experience (AWS, K8s, CI/CD) — advantage.