Applied AI Engineer – Sidekick

About[monday.com

](http: //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: Sidekick is [monday.com

](http://monday.com)’s AI assistant, used by 2M+ people to plan, analyze and get work done across the platform. We’re a small, senior group that turns the latest agentic research into features that run reliably at scale, and we own them end to end: from early prototype to production quality.

About the role:

• Design, build and ship production AI agents: tool use, multi-step reasoning, memory and context management

• Bring state-of-the-art agentic techniques into the product

• Own agent quality: build offline evals (golden datasets, LLM-as-judge, regression suites) and online metrics, and drive improvements you can measure

• Balance quality, latency and cost in production, with solid observability and tracing

• Work with product and design to turn open-ended goals into shipped AI features

Requirements:

• 4+ years of software engineering experience, including hands-on work shipping AI agents or LLM-based features to production

• Hands-on experience with agent frameworks (e.g., Lang Graph, Vercel AI SDK or Claude Agent SDK) and core agentic patterns: tool calling and MCP, structured outputs, context management

• Experience evaluating AI agents and LLM-based features, offline and online, to measure and improve quality over time

• Comfortable owning ambiguous, open-ended problems end to end, from exploration and prototyping to production, with limited direction

• Keeps up with a fast-moving field and adopts new techniques where they make a real difference

Nice to have:

• TypeScript/Node.js (the team’s primary stack)

• High-scale data infrastructure: Kafka, Cassandra, MySQL, CDC

• Full-stack experience (React)

• Background in data science or applied ML