monday.com

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 RevAI is the team building the AI agents inside monday.com's revenue organization, as part of BigBrain, monday.com's internal data and AI group. Our mission is to reinvent how monday.com's Sales and Customer Success organizations work, making them truly agentic end to end, from the first touch with a lead all the way to closing the deal and supporting customers. Our agents book meetings, run outbound, handle inbound leads, and help sales reps manage their accounts with AI-generated account plans, next-best actions and ready-to-send drafts that write straight back to the CRM. We work closely with the business: sales, RevOps and GTM leadership. That means we understand the business process first, then turn it into agents running in production. Our agents run on an agentic platform we built in-house. It is event-driven and operates across hundreds of thousands of accounts, so LLM cost, latency, reliability and business impact are everyday problems for us. We're a small team with high ownership and low ego, and we prefer to just try things rather than wait for permission. About the Role Lead a team of AI software engineers: mentor and grow them, set priorities, and own delivery from planning to production Design, code and ship AI agents and agentic systems alongside the team Work closely with the business, partnering directly with sales, RevOps and GTM stakeholders to understand revenue processes, find high-impact opportunities, and turn business needs into agents with measurable outcomes Own the technical direction of our in-house agent platform and the agents running on it: architecture and design docs, event processing and orchestration, policies and guardrails, human-in-the-loop flows, and tool integrations Integrate LLMs in production through an AI gateway, and tune model routing, prompt caching, token budgets and rate limits for scale, cost and quality Build and harden integrations with CRM and GTM systems (e.g. Salesforce, email, voice and messaging providers, scheduling tools) Set the bar for engineering quality and reliability, including code reviews, monitoring and alerting, incident response, and resilient long-running workflows Manage expectations and communicate progress, trade-offs and impact to stakeholders and leadership Requirements 5+ years of software engineering experience in the industry, shipping production systems Experience leading or mentoring engineers, either as a team lead or as a strong tech lead who is ready to step into management Strong server-side expertise in TypeScript/Node.js (or similar), with experience building microservices, APIs and distributed or event-driven systems at scale Proven experience shipping LLM-powered features or AI agents to production (prompting, tool calling, evaluation, cost/latency trade-offs) Previous experience building agents and workflows with frameworks and tools such as LangChain/LangGraph, n8n or similar Strong business acumen and comfort with revenue/GTM processes (lead management, sales pipeline, account management), with the ability to translate business problems into technical solutions Proven stakeholder management, working directly with non-technical partners and aligning priorities across teams Strong ownership and observability mindset, and comfort debugging production issues end to end Excellent communication skills, team mindset, and a bias for action Nice to Have Experience with Salesforce or other CRM/GTM platform integrations Background in sales engineering, solutions engineering, or other customer-facing technical roles Familiarity with agent frameworks and patterns (multi-agent orchestration, memory, evaluation, guardrails) Experience with React and micro-frontend architectures Experience with Kubernetes, AWS and CI/CD Experience with data pipelines and workflow tools (e.g. Airflow, Python, Snowflake) Background in voice or conversational AI If this sounds like your kind of challenge, we're looking for an AI Software Engineer Team Lead to build and lead the team shaping how AI agents drive revenue at monday.com. We believe in equal opportunity. At monday.com, we believe everyone should feel they belong - exactly as they are. We're an equal opportunity employer, committed to an open, accessible, and inclusive workplace free from discrimination or harassment of any kind. All qualified candidates will be considered for employment, regardless of race, color, religion, nationality, sexual orientation, gender identity, age, marital status, pregnancy, family or parental status, disability, veteran status, or any other characteristic protected by law. If you need support or accommodation during the hiring process, we're here to help. Meet the R&D team The R&D Team is passionate about building innovative and lovable products, while tackling complex engineering problems at a great scale. We're accountable for bringing the company's vision to life by navigating our progress into flawless execution and encouraging full ownership and independence in all projects.

Luna is a new startup inside monday.com Agent Labs, founded and run by monday.com's CEO, the program that spins up independent startups from scratch. Each one runs like a seed-stage company: a tiny team, a real product, real users, with monday.com's backing and distribution. Luna already has a live product, a pile of open problems nobody has answered yet, and no layers between you and the person making the calls. We're hiring the engineer who builds it. You work directly with the founder, monday.com's CEO. Decisions happen in the conversation, not in a roadmap review. You own the engineering. The founder owns the product. What we're building Meet Luna, the first generation of autonomous agents, which proved that agents can do real work. It also proved they broke. Unbounded self-coding that can touch any key. Everything is riding on raw LLM reasoning, so execution drifts. No way to see what actually happened. Luna is the second generation. It still learns and improves itself, but on a scaffold built for trust: Deterministic workflows, the agent writes and refines, then runs on a real engine instead of re-reasoning every time. A one-way vault. Secrets resolve below the plugin layer and never enter the model's context. Rollback on every change, an audit trail on every action, and approval gates on anything sensitive. Everything else is a plugin: tools, channels, skills, isolated per agent. Luna isn't a chatbot. You describe the goal, it builds the workflow, you correct it, and it runs reliably next time. A private Luna spins up in about a minute today. There's no playbook yet for what a good agent is in this context. We're writing it with real use cases and real constraints. That's the job. Who we're looking for An experienced builder at heart. You'd rather ship the thing than pitch it. This is an engineering role, not a founder track. Instincts about agents. Before writing a line, you ask what the model must never be allowed to touch, how you'd know it failed, and what happens when it does. Shipping ten agents isn't required. Having thought hard about one is. Independent. Hand you something vague, and you come back with something that works. Strong fundamentals in distributed systems and reliability, with production experience. Nice-to-have: LLM tooling in production, tool use, sandboxing, and evals. A security-minded way of building.

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 role monday.com's AI platform is moving fast — new agents, new capabilities, new pricing — and every team in CCO needs to stay sharp on what's new, what it means, and how to use it. This role owns that mission. You'll be the deep AI product expert for our CCO Academy. You work directly with Product and Engineering, stay ahead of every release, and translate what you know into knowledge the whole group can act on. You're not a passive documenter — you're a multiplier. You write the guide, run the webinar, present the release, and make sure the whole team walks away smarter. Responsibilities Own the AI knowledge infrastructure for CCO: maintain accurate, up-to-date knowledge on AI features, agents, pricing, and positioning. Stay ahead of every product release — translate new capabilities into structured enablement content before they ship. Deliver knowledge to the group through live formats: run internal webinars, present product updates, lead knowledge sessions — you're comfortable in front of an audience and make complex content engaging. Upskill the CCO Academy group through a mix of written resources and live delivery — make the whole team genuine monday AI experts. Embed in your assigned POD and provide the product intelligence that drives their enablement work. Proactively identify knowledge gaps and close them before they become blockers. Contribute to agentifying the documentation and release communication process. Requirements 2–4 years in product knowledge, technical writing, product enablement, or customer education at a B2B SaaS company. Genuine depth of curiosity about AI products — you want to understand how agents work, not just what they do. Strong ability to translate technical complexity into clear, accessible content for non-technical audiences. Confident presenter: you're comfortable running a room, delivering webinars, and presenting product updates to groups of all sizes — you make the complex feel clear and the dry feel engaging. Organized and systematic: you build processes, not just documents. Comfortable working cross-functionally with Product, Engineering, and business teams. Fast learner: monday's AI platform moves quickly, and so will you. Nice to have: experience with knowledge management systems; background in AI or technical products; experience building self-serve learning resources. What monday.com can offer you Join a customer-obsessed team where transparency and ownership are how we actually operate - not just things we put on a wall. Work on a multi-product suite powered by advanced AI, where what you ship reaches hundreds of thousands of customers worldwide. Competitive salary, benefits, bonus potential, and equity eligibility for many roles — we believe people should share in our success. Grow fast through a dedicated L&D team, AI workshops, bootcamps, and internal hackathons - the industry moves quick and so do we. A collaborative, global culture backed by Employee Resource Groups and workplace teams across New York, Tel Aviv, London, Munich, Warsaw, Tokyo, Sydney, and more. Meet the Operations team The Operations Team collaborates with the entire company globally and provides advice and guidance to enable and empower all teams in initiatives related to IT, facilities, event management, social impact, our makers and more. We take a creative approach in order to scale and optimize internal processes. We are a crew of energetic and caring individuals who love using teamwork to solve complex problems in a fast-paced environment.

Meet render.ai, monday.com's new AI venture. At render.ai, we're redefining how humans use AI for work. render.ai enables anyone to bring ideas to life in minutes, using their words. We're a small, autonomous team - closer in spirit to an early-stage startup than to an established company. There's no fixed playbook: we're still figuring out what the product looks like, and every engineer helps shape that, not just build it. What are we looking for? You love prompt engineering for LLM and image generation, chasing high-fidelity outputs at scale, and you know how to push foundation models further than most think possible. You own the model quality lifecycle end-to-end, from early experiments to production monitoring, turning the latest LLM breakthroughs into systems that hold up at scale. You build evaluation frameworks you can trust, offline tests, and A/B experiments that turn feedback into real, measurable improvements. You keep a close eye on live AI systems, watching latency, hallucinations, and drift, and get ahead of failure modes before they become real problems. You're genuinely strong in TypeScript and Python, comfortable moving between fast AI experimentation and solid production engineering. You like getting hands-on with data, sourcing and cleaning it to make prompts, models, and evals better. You're energized by ambiguity and fast-moving environments, always curious about the newest models and techniques on the frontier. You're excited about where this goes next, helping render.ai expand into new modalities like voice and video. Advantages: Experience with modern LLMs and image models such as Flux and Imagen. Experience building AI-native or agent-based products from scratch. Familiarity with LLM observability tools, tracing, and debugging workflows. Background in rapid prototyping, experimentation, or startup-like environments.

Meet Harmony, Monday.com's new AI venture. We're redefining how businesses interact with their customers through next-generation conversational AI and agentic systems. Harmony doesn't just react- it plans, reasons, and acts. You'll join a small, highly autonomous team with the agility, ownership, and pace of a startup, working alongside world-class engineers and researchers to build the next generation of conversational AI. You'll have access to large-scale real-world data, the compute and resources to pursue groundbreaking research, and the freedom to move fast while helping shape our AI vision. About The Role - Research novel algorithms and design new deep learning architectures to advance our in-house NLP and conversational models. - Develop methods for translating customer goals into structured representations with controlled states and real-time observations. - Help design the reasoning layer that orchestrates our AI models efficiently alongside a range of LLMs, enabling each agent to adapt its policy throughout a conversation while remaining aligned with customer objectives. - Build analytical tools that trace our AI decision process across a vast corpus of conversations, providing clear visibility into their reasoning and behavior. - Collaborate closely with engineers and product teams to translate cutting-edge research into production at scale. - Proactively lead new ideas and technical initiatives. Requirements - MSc or PhD in Computer Science, Mathematics, Physics, Electrical Engineering, or a closely related field. - Proficiency in Python. - Strong theoretical background in machine learning and deep learning principles. - Solid understanding of NLP concepts and relevant linguistic principles (co-reference, natural language inference, grammatical relations, and similar). - Experience using statistics and information theory to evaluate AI models and conduct EDA. - 4+ years of experience conducting NLP research with deep learning models and frameworks (PyTorch, TensorFlow, and similar). - Experience shipping AI systems from research to production. - Experience with conversational AI agents is a big plus. - Publications at top-tier conferences (ACL, EMNLP, NeurIPS, ICML, CVPR) are a plus.