---
title: 'Data Scientist– AI Infra & Evaluation Foundations at monday.com'
canonical: 'https://feeny.ai/job/data-scientist-ai-infra-evaluation-foundations-monday-com-tel-aviv-yse6dkrrv619'
type: 'job'
last_seen: '2026-11-05'
---

# Data Scientist– AI Infra & Evaluation Foundations at monday.com

- **Company:** [monday.com](https://feeny.ai/companies/monday-com)
- **Location:** Tel Aviv, Israel
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-09-24
- **Last confirmed live:** 2026-11-05
- **Apply:** https://jobs.ashbyhq.com/monday.com/c63d83ff-8462-48f6-8c27-692f903c28a5

## Job description

About monday.com: [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.

## About the team

The AI Infra group builds the foundations, tools, and platforms that every team at monday relies on to ship intelligent, agentic features. We own the core infrastructure—including the AI Gateway and our centralized Evals framework—ensuring every AI feature deployed to production is secure, resilient, cost-effective, and above all, trustworthy.

Our focus is on the frontier of agentic AI: dissecting complex agent trajectories, building robust evaluation frameworks, and turning subjective notions of "good AI" into rigorous, actionable metrics. As a Data Scientist on this team, you will bridge the gap between AI research and production infrastructure. You'll partner closely with engineering and product teams across monday to design the judges, metrics, and error analysis workflows that allow us to ship cutting-edge AI agents with speed and confidence.

This position is based at our Tel Aviv office (Headquarters).

About the role: As a Data Scientist in AI Infra, your goal goes far beyond simply building an evaluation framework—you will own the organizational impact of how monday evaluates and trusts AI. You will define how teams measure quality, influence engineering decisions across R&D, and turn fuzzy notions of "good AI" into numbers product teams rely on to ship with confidence.

- Own the evaluation methodology: Design metrics, pipelines, and methodology that teams across monday trust and adopt as their source of truth.
- Transform the AI agent lifecycle: Standardize how AI agents are built, regression-tested, and maintained across the org, embedding continuous evaluation into everyday engineering workflows and post-deployment monitoring.
- Drive organizational impact & enablement: Partner with AI feature teams across monday to translate domain expectations into meaningful datasets, test suites, and continuous evaluation pipelines—leveling up engineers and product managers along the way.
- Build hands-on tools: Prototype and stand up eval pipelines end-to-end, bridging the gap between ambiguous, high-level product requirements into clear, quantifiable evaluation standards that become central to how features are greenlit for production
- Anticipate future failure modes: Stay ahead of evolving agent architectures by proactively designing next-generation evaluation strategies.

Requirements:

- Agentic Systems & Architecture:
- 3+ years of experience as a Data Scientist in non-academic settings working with complex production running AI systems. Familiarity with current agentic frameworks like LangGraph, LangChain, and SoTA SDKs.
- Deep, practical understanding of how agents operate - models, context, capabilities and harnesses. Deep experience with agentic evaluation methodologies
- Execution, Code & Trace-First Mindset:
- Production-grade coding skills with a track record of building, prototyping, and shipping end-to-end data or eval pipelines,
- A "trace-first" diagnostic mindset—comfortable diving into raw agent execution logs, inspecting failure modes, and constructing qualitative error taxonomies.
- Product & Organizational Impact:
- Strong product intuition and exceptional communication skills to translate complex evaluation data into clear, actionable guidelines.
- Proven ability to partner closely with software engineers and product teams, taking ownership of driving adoption and raising the quality bar across the organization.

## Preferred Qualifications

- Direct experience designing evaluation strategies for complex agentic systems in production
- Prior experience working within centralized platform/infra teams that support multiple product verticals.
- Experience contributing to modern microservice architectures, GitHub workflows, and automated production CI/CD pipelines
- Familiarity with modern agent and eval tooling and observability stacks (e.g., LangSmith, Langfuse, or custom internal platforms).
- Knowledge of TypeScript or experience working within modern platform architectures.
- Master’s degree in Computer Science, Data Science, Statistics, Engineering, or a related quantitative field.

## About monday.com

## Company Overview
- **One-liner**: monday.com is a global software company that develops a browser-based AI work platform to help teams manage their work, automate processes, and achieve more together.
- **Entity Type**: Public (Nasdaq: MNDY)
- **Headquarters**: Tel Aviv, Israel (with major offices in New York, London, Warsaw, Tokyo, Singapore, Melbourne, and Munich)
- **Founded**: February 2012 (originally as dapulse, rebranded to monday.com in 2017)
- **Founders**: Roy Mann and Eran Zinman

## Core Business
- **Primary industry/industries**: Process management, project management software, productivity software, team management, customer relationship management (CRM), collaborative software
- **Target customers**: B2B - serving over 250,000 customers globally, including over 60% of the Fortune 500
- **Mission or purpose statement**: "Shape how the world works" - helping teams get more work done with AI-powered tools that automate, build, and scale impact end-to-end.

## Products & Services
- **monday.com Work OS**: The core platform, a customizable, no-code work operating system for managing projects, workflows, and processes across teams and departments.
- **monday AI Platform**: An enterprise-grade AI infrastructure that allows users to build and deploy AI agents to automate tasks, with features like simulation mode, full user control, and a guarantee that customer data is never used to train AI models.
- **monday CRM**: A customer relationship management solution built on the Work OS.
- **monday Dev**: A product management tool tailored for software development teams.
- **monday Sales CRM**: A dedicated CRM for sales teams.
- **monday Marketer**: A work management solution for marketing teams.
- **Open API & Integrations**: An open platform allowing third-party developers to build custom views, dashboard widgets, automations, and integrations with other work apps.

## Market Standing
- **Valuation/Market Cap**: As a public company, market cap fluctuates. During its last private round in 2019, it was valued at $1.9 billion. The company went public in June 2021.
- **Key Metric**: Over $1.232 billion in annual revenue (2025), with over $1 billion in ARR.
- **Notable Investors/Partners**: Insight Partners, Sapphire Ventures, Hamilton Lane, HarbourVest Partners, ION Crossover Partners, and Vintage Investment Partners were key investors in its growth rounds.
- **Growth Signals**: The company has grown to over 3,155 employees (2025), serves over 250,000 customers, and is trusted by over 60% of the Fortune 500. It is aggressively expanding its AI capabilities with its new AI work platform and agent features.

## Competitive Advantages
- **Platform Stickiness**: monday.com is a highly customizable, no-code platform that becomes deeply embedded in a customer's daily workflows, creating high switching costs.
- **Data Privacy & Trust**: The company explicitly states that customer data is never used to train AI models, a major differentiator for enterprise clients concerned with data security.
- **Enterprise-Grade Security**: Offers robust security, governance, permissions, and compliance features, making it a trusted partner for large organizations.
- **Strong Brand & Scale**: With over 1 billion in ARR and a massive customer base, the company has significant resources for R&D and market expansion.

## Strategic Focus
- **AI-First Platform**: monday.com is pivoting heavily to become "The AI Work Platform for People & Agents," allowing users to build, validate, and deploy AI agents to automate work. This is the company's primary growth vector.
- **Expanding Enterprise Footprint**: Deepening its penetration into large enterprises by offering a secure, scalable, and customizable platform.
- **Product Ecosystem Growth**: Continuously expanding its suite of specialized products (CRM, Dev, Marketer) to capture more of the enterprise software market.

## Why Work Here
- **Product-First Culture**: The company is deeply committed to building intuitive, powerful, and easy-to-use products that solve real customer problems.
- **Impact & Ownership**: Employees are given significant ownership over their work from start to finish, fostering a culture of personal investment and high impact.
- **Hybrid Work Model**: monday.com offers a hybrid work environment, with most teams spending three days a week in the office for collaboration and the rest working remotely.
- **Career Growth**: The company provides learning programs, mentorship, development opportunities, and an internal mobility process to support diverse career paths.
- **Global & Diverse Team**: With 3,000+ employees across 15+ locations and 17 teams, the company offers a truly international and diverse work environment. It is an equal opportunity employer committed to inclusion.
- **Strong Financial Health**: As a profitable, publicly-traded company with over $1B in ARR, monday.com offers stability and long-term growth potential for its employees.

## Sources
1. [monday.com Careers Page](https://monday.com/careers)
2. [monday.com Official Website](https://www.monday.com/)
3. [Built In - monday.com Company Profile](https://builtin.com/company/mondaycom)
4. [Wikipedia - Monday.com](https://en.wikipedia.org/wiki/monday.com)
5. [LinkedIn - monday.com](https://uk.linkedin.com/company/mondaydotcom)

## Other roles at monday.com

- [Software Engineering Tech Lead](https://feeny.ai/job/software-engineering-tech-lead-monday-com-warsaw-hxy41vksk9y2) — Warsaw, Poland
- [Software Engineer Tech Lead – AI Workflows & Automations](https://feeny.ai/job/software-engineer-tech-lead-ai-workflows-automations-monday-com-tel-aviv-5sck134zwndn) — Tel Aviv, Israel
- [Enterprise Account Manager](https://feeny.ai/job/enterprise-account-manager-monday-com-london-9zxy0khm0w3y) — London, United Kingdom
- [Product Marketing Manager, AI Builder](https://feeny.ai/job/product-marketing-manager-ai-builder-monday-com-tel-aviv-x2x548nqr14j) — Tel Aviv, Israel
- [Forward Deployed Consultant](https://feeny.ai/job/forward-deployed-consultant-monday-com-singapore-343eep63ymvh) — Singapore
- [Forward Deployed Engineer](https://feeny.ai/job/forward-deployed-engineer-monday-com-denver-me8t5gwwwqas) — Denver, CO
- [Field Marketing, BR](https://feeny.ai/job/field-marketing-br-monday-com-brazil-09sw1544pj2s) — Brazil
- [Strategic Account Manager](https://feeny.ai/job/strategic-account-manager-monday-com-london-n49wx74j8zhh) — London, United Kingdom
- [AI Solutions Builder](https://feeny.ai/job/ai-solutions-builder-monday-com-tel-aviv-tr7dhandq8vc) — Tel Aviv, Israel
- [Solution Architect - APJ](https://feeny.ai/job/solution-architect-apj-monday-com-sydney-rwzh3nb6m2mk) — Sydney, Australia