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Open nowPosted 16 hours ago

AI Solutions Builder

monday.com124 open roles

Where
Tel Aviv
Work mode
Hybrid
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Your applicationOpen nowAI Solutions Buildermonday.com · Tel Aviv
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The clock on this job

Early applications get read.

12.3% of postings close within 7 days. Measured by our own scanner across the market. monday.com postings stay open a median of 11 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.3%7 days
  4. 19.3%14 days
  5. 35.6%30 days
  6. 58.1%60 days
This job: posted 16 hours ago

monday.com median: 11 days open

The posting

monday.com http://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.

Our revenue organization just redesigned itself around AI -not as an add-on, but as the engine. The AI backbone now carries knowledge, content, communications, onboarding and gap resolution across every region, 24/7, without a human dispatcher. We built the prototype ourselves and it works. This role is who we hire to make it real infrastructure.

The Center of Revenue Excellence (CORE) is built on a simple premise: AI carries the scale, humans carry the judgment. Our Platform & Knowledge team decides what the revenue org needs to know and how it should learn it. You build the systems that deliver it -and you own whether they stay healthy.

About The Role

- Build the AI backbone. Knowledge agents and their modes, agentic onboarding, AI simulations, AI-run certifications, content generation at scale, automated comms, and knowledge application analytics. Eight live components today, and a roadmap with room for more.

- Own the health of the system. Not just shipping — reliability, accuracy, cost, and uptime on infrastructure the entire revenue organization depends on. This is the part of the job nobody else can do for you.

- Scope before you commit. Analyze what's technically and economically possible, tell us honestly what a capability will cost to run, and say when something shouldn't be built at all.

- Turn business problems into build specs. Take a requirement at 30,000 feet — business logic, audience, desired end experience — and come back with something buildable, sequenced MVP first.

- Think past the brief. Surface the requirement nobody asked for but everybody needed. The team defines what and why; you're expected to shape how, and to push back when the how reveals a problem with the what.

- Roadmap everything you build. Every component is a product with real users, a feedback loop, and a next version. Nothing gets built once and abandoned.

- Rally the stakeholders. An agent nobody adopts is a failed build. Getting there means data access, named content owners, permissions, and the right questions asked of the right people — often before anyone sees a line of code.

- Partner with engineering. Work with BigBrain and BizApps where a build exceeds what one person should carry — and document and architect so that nothing critical depends on you alone.

- A real example of the work: reps in one region aren't running AI discovery well. Telemetry confirms it's global, not local. The team scopes the gap and defines the solution -a new mode for our knowledge agent, "Disco Coach." You take that spec, decide how it actually gets built, ship the MVP, and own it from there.

Requirements

- 4+ years building software, automation, or AI solutions in a fast-paced B2B SaaS environment. You don't need "engineer" in your title history — but this is not a junior role, and it is a genuinely technical one.

- Mastery of AI building tools, especially agentic. Proven, hands-on experience shipping agents and AI systems that real people use daily — LLM and agent frameworks, Claude Code or equivalent, MCP, retrieval and RAG patterns, no-code and low-code platforms. Familiarity with monday's own AI products is an advantage.

- Code-capable and comfortable in production. You write scripts, work with APIs and data, read logs, and debug things that break. You can maintain what you build without waiting for an engineering queue.

- Product manager instincts. You can look at a problem from 30,000 feet, translate business logic and end-user experience into a specification, scope an MVP, and hold a roadmap. You've owned something end to end, not just executed tickets.

- SaaS organizational fluency. You know how a software company works and who to go to. Experience in or alongside a sales organization is a strong advantage — client-facing, RevOps, sales systems, or solution engineering.

- Experience with enablement, training, or knowledge systems is an advantage — LMS, knowledge bases, search, certification or simulation tooling. Not a requirement.

- Stakeholder skill. You ask the right questions, understand who you're building for, and get the blocks in place so that what you ship actually gets adopted rather than admired.

- Ownership over handoff. You document, you make things maintainable, and you don't build black boxes only you can operate.

- Strong written and spoken communication — you can explain what you built, and what it can't do, to technical and non-technical audiences alike.

What monday.com http://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

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