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Productboard is the intelligent product management platform that helps future-ready product teams drive strategic alignm
The Role
Own the enterprise platform underlying Productboard’s agentic product system, including the data model, permissions, security, compliance, APIs, search, integrations, and core product services. Lead platform product strategy, roadmap, hiring, and cross-functional execution while making enterprise complexity invisible to AI product teams. Partner closely with engineering, enterprise sales, the CTO, and the Head of AI Product to deliver secure, explainable, scalable capabilities for customers and agents.
Summary Generated by Built In
Locations: Prague / Brno / Remote Europe
The role
Head of Product, Enterprise Platform. Reports to the CTO. Based in Prague, Brno, or remote within Europe with regular time in Prague.
The impact of this job in one sentence: the teams building our agents never think about enterprise complexity, because you solved it underneath them. Security, compliance, permissions, authorization, data storage and services, the integrations into a customer's CRM, and engineering tools are your problem, delivered as platform services. Most of these capabilities are exposed to customers as well, not only to the agent. The agent teams consume them and move on. Every hour they would have spent on those questions goes into making the agent better.
Productboard is the agentic product system for product teams. At its center is Spark, our product management agent. It connects to a company's customer feedback, strategy, competitive intel and codebase, finds the highest impact opportunities, writes delivery ready specs, and runs the workflows a team builds as reusable skills.
Spark, the agent harness and every skill run on the platform you own. An agent should be able to act without being wrong about who may see what, where data is kept and for how long, or what a customer has paid for. You make those answers true underneath it. The PMs on the platform surfaces report to you. Design for those surfaces comes from your AI Product peer's team.
What you own- The core data model and data services. The objects every feature and agent works with: products and features, goals, customers and segments, feedback, and how they relate. You decide what an object is, how objects connect, what an agent may write, how data is stored, queried, retained and exported, and what a customer can control about what an agent sees.
- Views, query and reporting engine. One query layer over the data model: filtering, grouping, aggregation, computed fields and saved views, served the same way to people, agents and the public API. Roadmaps, grids and dashboards are built on it by other teams.
- Scoring and planning primitives. Configurable scoring models, formulas and weights.
- The document editor. Where specs, notes and customer feedback live, for people and agents alike.
- Permissions, authorization, sharing and administration. Roles and access control for people and for agents acting on their behalf, sharing with people outside the workspace, and the admin controls a buyer checks before signing.
- Security and compliance. The product side of security questionnaires, residency, retention, audit logs, and the record of what every agent did, and for whom.
- Search. Finding anything in a workspace, whether a person or an agent is asking.
- Notifications and alerting. Routing, batching, subscriptions and delivery across in-app, email and the channels teams already live in, so agent generated activity reaches the right people without becoming noise. The notification experience sits with your AI Product peer.
- Explainable and provable agent work. Customers will not hand an agent their roadmap on faith. The evidence is yours: where an answer came from, which sources it used, why it acted, what changed as a result, and how a team measures whether the agent is getting better. Evals and quality signals ship as product surface. The eval suite itself sits with your AI Product peer.
- The enterprise ecosystem. Two-way integrations with the systems an enterprise already runs: CRM such as Salesforce and HubSpot, engineering tools such as Jira and Linear, feedback sources, data warehouses, and the public APIs partners build on. Field mappings, sync rules, auth scopes, rate limits and each customer's own schema are complexity you absorb, so an agent reads a customer record or writes a ticket and nothing more. The protocol layer that lets external agents call Productboard sits here; the specific tools exposed through it sit with your AI Product peer.
Our CEO owns product strategy: where the product goes and why. You own the roadmap and decisions for your domains within it. Engineering managers own the engineering side of each domain and your PMs and designers partner with them. Initiatives are staffed from a shared roadmap; people move with initiatives, domains and reporting lines stay put.
Our Chief AI Officer sets direction and raises the bar on anything agentic. He owns no layer and no roadmap.
Your peer is the Head of Product, AI Product. They own Spark, the harness, skills, AI quality, feedback analysis, specs, and the tools exposed to external agents. Everything they ship reads and writes your data model, your permissions and your editor. Agent work that touches your domains is staffed across both groups. Their requests arrive faster than you can build; your job is to turn them into platform capabilities, not one-off fixes.
Your other constant partner is enterprise sales. Security reviews, procurement questions and admin requirements come to you, and the answer is usually a product decision, not a document.
You bring the problem before the solution. An initiative of yours gets investment once you have made the case that the problem is worth solving. You ship it to our own workspace first and take it GA when it hits the goal you set at the start.
Why this matters for your careerEvery platform that has put an agent on top of its product has had to answer the same questions underneath it. What a permission model means when the actor is an agent working for a person. How a data model stays trustworthy when most writes are not human. How a customer's security team audits work no employee did, what it cost, and why the agent did it. What stays a screen and what becomes a capability.
Here you answer them with the agent running on your platform, so a gap you leave shows up in its behavior the same week. Enterprise customers sit in the loop, and their security reviews and contracts hold you to what you ship. The agent team sits next to you, so you see within days what each platform decision does to the agent. After a year you will know how to get an enterprise to trust an agent with its data, because you will have done it, in production, with customers who checked.
Our north star: get from idea to learning twice as fast. More experiments. Faster learnings. Better outcomes. We win by deciding faster with better evidence.
First six months- The data model is written down once: what every entity means, how entities relate, what an agent may write. AI Product builds on that document.
- The enterprise controls run as platform services: who may see what, where data lives and for how long, what a plan allows, what every agent did. An agent acting for a person sees and changes exactly what that person could.
- Every part of the platform has a product manager, and the seats still open when you arrived are filled by people you hired. Every part also has a decision on its future, stay, merge or retire, and the roadmap reflects it.
- The top three capabilities AI Product asked for have shipped as platform capabilities, each used by at least two surfaces.
- The CRM and engineering tool integrations have an owner and a roadmap.
In the order we weight it.
- You have built a platform other products stand on, and hidden its complexity from them. You have owned a data model, a permission system, a compliance surface or an API that other teams built against without having to understand it, and you know the cost of getting the abstraction wrong.
- You have a computer science or engineering background. You own the data model, the permission system and the API, and those conversations go faster when you can read an entity diagram, a query plan and an API spec yourself and argue with an engineer about them.
- You build with agents every day. You use Claude or its equivalent for real work, connected to your own tools and data. You know what an agent needs from a platform because you have felt what happens when it is missing.
- You are fluent in headless. The platform will be used through agents, open agent protocols and other tools. You can decide which capabilities need a screen and which need an API.
Shared benefits (all EMEA)
- 5 weeks of paid time off per year
- 9 paid sick days per year, also for mental-health days
- 1 paid Volunteer Day per year
- Stock options
- USD 300 per year professional development stipend
- Mental wellness program with online therapy sessions
- Carrot: fertility, adoption and family-forming support for you and your partner (pregnancy, postpartum and menopause support in the UK and Ireland)
- One-off home-office stipend (amount by location)
- Monthly fitness or wellness support (form by location)
- Free 1Password Families account
- Annual company retreat and team off-sites
Prague benefits
On top of the shared benefits:
- Multisport card, with options for a +1 and children
- Catered lunches in the office every working day, always with a vegetarian option
- Monthly office breakfast, plus snacks, coffee and drinks in the kitchen
- Dog- and kid-friendly office
- T-Mobile phone plan
- 14 days of paternity leave at full pay
- One-off home-office stipend of up to CZK 7,000
- Tickets to Prague Zoo
- Day camps for employees' children during school breaks
Health insurance and pension are statutory in Czechia, so there is no private plan here.
Relocation OpportunitiesIf joining us means making a move, we're here to help make that transition easier.
Candidates must have the legal right to work in the EU. While we are unable to provide visa sponsorship for this role, we're happy to support relocation to Prague for candidates already authorized to work in the EU.
Relocation Support
We offer a one-time relocation bonus ranging from $6,000 to $13,000 USD, depending on your personal situation, whether you're moving on your own or with a partner or family.
This bonus is intended to help offset moving expenses and support your transition into your new city. While it may not cover every cost, it provides meaningful financial support as you get settled.
If you're thinking about relocating and want to explore what this could look like for you, we'd be happy to have that conversation.
About ProductboardProductboard is the leading intelligent product management platform, used by 6,000+ companies including Salesforce, SAP, Autodesk, and Kroger. Headquartered in San Francisco, with engineering hubs in Prague and Brno. Backed by Index Ventures, Kleiner Perkins, Sequoia Capital, Bessemer, Tiger Global, and Dragoneer.
We've spent the last decade building the foundation for how product teams work. We're now in our 0-to-1 moment again, building Productboard Spark — the AI-first, agentic experience that turns raw feedback and signals into clear problems, strong specs, and faster execution. Spark is what powers everything you'd be working on.
Are you building with us?
If the work above is what you want to spend the next chapter of your career on, apply below!
Equal Opportunity
Productboard is an equal opportunity employer. We are committed to an inclusive hiring process and consider all qualified applicants without discrimination based on characteristics protected by applicable law.
By applying you agree to Productboard's Global Candidate Privacy Policy.
Skills Required
- Experience building and owning a platform that other products or teams depend on, including data models, permission systems, compliance surfaces, or APIs.
- Computer science or engineering background with the ability to understand entity diagrams, query plans, and API specifications.
- Hands-on experience building and using AI agents with connected tools and data.
- Fluency in headless product experiences, APIs, agents, and open agent protocols.
- Legal authorization to work in the European Union.
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The Company
What We Do
Productboard is the intelligent product management platform that helps future-ready product teams deliver exceptional products with clarity and confidence. Over 6,000 companies, including Salesforce, Autodesk, Zoom, One Medical Group, Cartier, and The Coca-Cola Company use Productboard to uncover customer needs, drive strategic alignment, and rally everyone around the roadmap. With offices in Prague and San Francisco, Productboard is backed by leading investors, including Index Ventures, Kleiner Perkins, Sequoia Capital, and Bessemer Venture Partners. Learn more at [www.productboard.com](http://www.productboard.com/)
Why Work With Us
We believe that truly great products are not created by individual geniuses but by a great group of people that leverages everyone’s curiosity and creativity. That is why our mission at Productboard is to **make products that matter, together**. We are a global company with a stimulating, multicultural environment.
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