Applied AI Engineering Tech Lead (TLV)
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Key details
Job Description
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:
Join the Sidekick group building monday's generative-AI capabilities for 2M+ users. You'll design and ship production LLM agents — bringing state-of-the-art agentic techniques into the product and owning AI features end-to-end. (placeholder intro — refine to taste)
About the role:
Design, build, and ship production LLM agents and agentic features, end-to-end
Bring state-of-the-art agentic techniques into the product — prototype, evaluate, productionize
Own agent quality through evaluation (offline + online) and drive measurable improvements
Partner with product and design to turn open-ended goals into shipped AI features
Requirements:
3+ years of software engineering experience, with hands-on experience deploying LLMs or AI agents in production
Proven hands-on experience designing and shipping production LLM agents — multi-step agents with tool-use, retrieval and/or memory — using modern agent frameworks (e.g., LangGraph, Vercel AI SDK,
or Claude Agent SDK), with a demonstrated habit of adopting state-of-the-art techniques as the field evolves
Experience with agent/LLM evaluation, both offline and online, to measure and improve quality over time
Comfortable owning ambiguous, open-ended problems end-to-end — from exploration and prototyping through to production — with limited direction
Works effectively with product and design, owning AI-based features end-to-end
Preferred:
TypeScript/Node.js (the team's primary stack)
Nice-to-have:
High-scale data infrastructure- Kafka, Cassandra, MySQL, CDC
Full-stack / React
Broad awareness of the agent-building landscape — frameworks, emerging patterns, and where the field is heading
Audit details(provenance, verification trail, raw fields)
Core fields
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mondayVerification trail
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