Director, AI Product Development

• Experience building on or for sales AI or GTM platforms, or in the Salesforce ecosystem.
• Experience with knowledge graphs, entity resolution or other data products where the quality of the underlying data shapes the user experience.
• Experience designing or delivering customer training, enablement or bootcamp programs.
• Prior experience at a top-tier consulting firm (McKinsey, Bain, BCG), advising CxOs and influencing large scale transformations.
• Experience working with distributed teams across the US and globally.

• Define the product experience. Turn our product strategy into agentic workflows that sellers and sales leaders rely on every day. Bring clear, opinionated judgement on what we build, what we do not build and what good looks like, and use adoption and business impact to decide what to build next.
• Build on the World Model. Design how sellers work in our CRM layer: opportunities that start on companies already in the World Model rather than on empty records, actions and outcomes captured as they happen, and pipeline and forecasting that run alongside a customer's existing CRM.
• Partner with Data & Insights. Work closely with the team that defines and maintains what Databook knows about every kind of company. Make sure the coverage, freshness and confidence of that data show up in the product where sellers need them, and that the gaps you see in customer questions shape what the team collects next.

• Design, build and ship AI applications. Partner with Applied AI engineering to take agentic workflows and next best action recommendations from concept and prototype through evaluation, testing and production release, and keep improving them once they are live.
• Lead and grow the Agent Builder team. Lead and develop a team of Agent Builders, growing in 2027, who configure our agentic workflows and build quality assurance into them. Set the standard for how that work gets done.
• Build quality into every workflow. Define what quality means for AI output a seller will act on, and make it measurable through evaluation sets, acceptance criteria, regression testing and production monitoring.

• Stay close to customers. Spend time with sellers, sales leaders, marketing, customer success, enablement and RevOps teams at our enterprise customers. Understand where deals are won and lost, and bring that reality back into the product.
• Partner with GTM. Work with our AI Strategy & Deployment team, who run customer deployments, so that what we sell, build and deliver stay aligned. Turn patterns from the field into reusable product capabilities rather than one-off customization.
• Educate customers. Help design and deliver our AI Bootcamps (roughly one week per quarter), teaching customer sales and enablement teams how to work with AI and get the most from Databook.

• Customer immersion. You have spent time with a range of our enterprise customers, observed their sellers at work, and can explain where Databook creates the most value and where it falls short.
• A product point of view. You have developed and tested new product concepts with the CEO and customers, and agreed priorities with Applied AI, Data & Insights and GTM.
• A quality bar in place. Every new workflow ships against an agreed evaluation and QA standard, and you can report on output quality across live customers.
• A team with a clear operating model. You have taken ownership of the Agent Builder team with a defined way of building, testing and handing off workflows, and you have taught in your first AI Bootcamp.

Databook is the AI guided selling platform and decision-support system built for enterprise GTM teams. Its three-layer architecture—verified customer-back intelligence, structured agentic reasoning, and guided coaching with closed-loop analytics—gives revenue organizations the consistency, confidence, and leadership visibility they need to win complex enterprise deals. Databook's customers drive more than $500B in annual revenue and include Salesforce, Microsoft, Databricks, Konica Minolta, and Schneider Electric. Learn more at www.databook.com http://www.databook.com.

Role summary: Build the revenue operating system for enterprise selling

For twenty years, enterprise sales has run on Systems of Record: CRMs that capture what happened, but do little to help a seller decide what to do next. Databook is building the revenue operating system that replaces them. It starts from a shared World Model of the companies, people, strategies and events in the market, so every account arrives already understood. On top of it, Databook reasons over the account, the deal and the seller's context, links events over time, and recommends the next best action with the evidence behind it.

We are looking for a Director of AI Product Development to lead how that product is designed, built, tested and shipped for some of the largest sales organizations in the world. You will report to the CEO, spend real time with customers, work hand in hand with our Applied AI engineering, Data & Insights and GTM AI Strategy & Deployment teams, and lead a team of Agent Builders who configure our agentic workflows and build quality assurance into them. Customer deployments are run by our AI Strategy & Deployment team; your focus is the product they deploy.

This is not a technical product management role. We are looking for sharp judgement, a deep understanding of how enterprise selling actually works, and refined product taste: someone who can tell the difference between an AI output that is technically correct and one a CRO or seller will act on. You have shipped AI applications into enterprise production, you know the domain, and you want a leadership role where the learning curve is steep and the impact is direct, working with some of the most sophisticated go-to-market teams in the world.