AI Engineer – New Ventures

New Ventures at monday.com is expanding into new, AI-native product areas, and we’re looking for an exceptional AI Engineer to join our fast-moving, high-impact team. Our team develops new products from the ground up, combining startup velocity with the scale, reach, and engineering excellence of monday.com.

The team built workcanvas.com and workassets.ai, and continues to explore and launch new product ventures. As part of a small, highly talented engineering group, you’ll play a key role in shaping the AI foundations, agent architectures, and intelligent systems powering these products and future initiatives.

This is a rare opportunity to define how AI-native products are built at monday.com—from core infrastructure and agent orchestration to model quality, evaluation, and continuous improvement in production.

#LI-DNI

About The Role

New Ventures at monday.com is expanding into new, AI-native product areas, and we’re looking for an exceptional AI Engineer to join our fast-moving, high-impact team. Our team develops new products from the ground up, combining startup velocity with the scale, reach, and engineering excellence of monday.com.

The team built workcanvas.com and workassets.ai, and continues to explore and launch new product ventures. As part of a small, highly talented engineering group, you’ll play a key role in shaping the AI foundations, agent architectures, and intelligent systems powering these products and future initiatives.

This is a rare opportunity to define how AI-native products are built at monday.com—from core infrastructure and agent orchestration to model quality, evaluation, and continuous improvement in production.

#LI-DNI

Join a tight-knit team building the next generation of collaborative, AI-powered products. We experiment quickly, validate ideas fast, and ship frequently. You’ll collaborate with senior engineers, designers, and product managers to push the boundaries of what’s possible with modern AI.

What you’ll do:

Architect and build AI-native systems from 0 1, including autonomous agents and intelligent workflows
Design and implement agent orchestration frameworks (memory, planning, tool usage, self-reflection, and recovery)
Own the full lifecycle of model quality—from experimentation and evaluation to production monitoring and continuous improvement
Design and build evaluation frameworks (offline benchmarks, online experiments, A/B testing) to guide model and product decisions
Monitor production AI systems, tracking quality, latency, cost, and failure modes (e.g., hallucinations, drift), and drive iterative improvements
Rapidly experiment with models, prompts, and architectures, using structured evaluation to identify the best solutions
Translate cutting-edge LLM capabilities into reliable, scalable, production-grade systems
Collaborate closely with product, design, and full-stack engineers to shape AI-driven user experiences
Take ownership of AI features end-to-end—from research and prototyping to deployment and monitoring
Help define best practices for building, evaluating, and operating AI-native products across the organization

Our Tech Stack:

React (Next.js), Node.js, TypeScript, PostgreSQL, Google Cloud Platform (GCP), Cloudflare, and modern AI/LLM tooling.

Your Experience & Skills
Proven experience building and deploying production-grade AI systems (beyond prototypes or demos)
Strong software engineering foundation with 4+ years of experience in backend or full-stack development
Deep familiarity with modern AI tooling and ecosystems (LLM APIs, embeddings, vector databases, RAG pipelines)
Hands-on experience designing evaluation and monitoring systems for LLM-based applications in production
Experience designing or working with agent-based systems (e.g., ReAct, tool use, multi-step reasoning loops)
Strong understanding of system design, scalability, and reliability in distributed environments
Experience running structured experiments (e.g., A/B tests, prompt/model comparisons) and using data to drive decisions
Ability to navigate ambiguity and rapidly evolving technologies
Strong communication skills and a collaborative, product-oriented mindset

Advantages:

Experience building AI-native or agent-based products from scratch
Familiarity with LLM observability tools, tracing, and debugging workflows
Experience with real-time systems, WebSockets, or collaborative environments
Background in rapid prototyping, experimentation, or startup-like environments
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