Senior Product Manager

Job description

**Are you ready to shape the future of data?** Matillion is the company behind[Maia](https://www.maia.ai/), the AI Data Automation platform. In the AI economy, demand for data is exploding. Manual data engineering can’t keep up. Maia fixes that by combining 15 years of data expertise with agentic AI to eliminate the manual work that slows data teams down. Organisations like Cisco, DocuSign, and Slack are already using it to deliver real business impact, faster. We started in Manchester and now we’re global - with teams across the UK, US and India and fifteen years of data expertise behind us. We have raised over $300M from some of the worlds' best investors, including General Atlantic, Lightspeed Venture Partners and Battery Ventures. We are driven, curious, energetic people who move fast, think big and hold ourselves to a high standard. We’re here to make a dent in the universe bigger than ourselves. And we’re looking for people who want to be part of it. **About the Role** As Senior Product Manager, you'll own a significant slice of the Maia product, working at the intersection of complex user problems, AI capability and commercial impact. We need someone who understands what a great agentic product experience looks like and holds the bar for it relentlessly. You will be user-obsessed and data-driven in equal measure. You define what success looks like before you build, run evals to hold Maia to a high bar, and use AI in your own workflow to move faster. We're not prescriptive about your background: what matters is that you can move fast like a startup and scale with discipline like a larger company, and you know the difference. Most of all, we're looking for depth: the instinct to get to the heart of a hard problem and own it end to end. Great product work happens through collaboration. You'll partner closely with Engineering and Design to build Maia, and with GTM to take it to market and turn what you learn into what you build next. ### What you will be doing - **Own a core area of Maia end to end:** define the problems worth solving, prioritise ruthlessly, make the hard trade-offs with incomplete data, and drive the work through to measurable impact. - **Set the quality bar for agentic behaviour:** build the evals that measure how good Maia really is, interrogate the outputs, and hold the line when it isn't there yet. - **Deeply understand our users:** get past feature requests to the real friction in a data team's workflow, and the moments that earn trust. - **Work at the frontier of the stack:** reason with Engineering about models, context, tools like MCP, and orchestration, and where each one changes the product. - **Accelerate your own output with AI:** use AI tools actively across research, synthesis, prototyping, and analysis, always finding ways to move faster without trading away quality. - **Drive cross-functional alignment:** work day to day with Engineering and Design, keep GTM ahead of what's shipping, and present your roadmap and priorities clearly to stakeholders, leadership and customers. ### What we are looking for - **A track record of shipping and scaling B2B products.** You have built, launched, and grown products people love. - **Real fluency with how modern AI products work.** You are familiar with evals, agentic workflows, context, and tools like MCP, and you have clear judgment about where AI earns its place and where it does not. - **A systems thinker.** You see how the pieces fit together and balance craft, speed, and commercial impact. - **Sharp judgment under ambiguity.** You turn incomplete information into crisp decisions, defend them, and change your mind when the evidence changes. - **Deep data literacy.** You are fluent with metrics and let evidence, not opinion, drive the call. - **Excellent communication.** You articulate a clear vision, bring cross-functional teams with you, and present with credibility to leadership and customers. - **Strong product instincts and taste.** You stay close to the user, know what great looks like, and hold the bar for it. - **Bonus: data domain knowledge.** Exposure to data integration, warehousing (Snowflake, Databricks), or analytics is a plus, not a requirement.