About this role
At Intuit, we're intentionally building AI into how we define, build, and ship products — and we're committed to equipping our teams to work at the forefront of it. We look for product managers who are excited to bring AI into their workflow — using it to move faster, go deeper on customer insights, and focus their energy on the decisions that only human judgment can make. We're looking for PMs who are curious, eager to experiment, and excited to continually evolve how they work.
You'll join the VEP Sales Technology Product Management team, where we lead AI-driven technology innovation to build platforms at scale that help transform the lives of consumers, small businesses, and accountants by connecting our customers to the experts and sellers who serve them across the full Intuit revenue lifecycle: from customer information and engagement, through pipeline and opportunity management, to quoting, contracting, and order fulfillment. Within that team, the Sales Data, Context & Intelligence group owns the foundation everything else is built on, turning our systems of record into connected, trustworthy context and intelligence that both sellers and AI agents can rely on to act with confidence.
We're hiring a Senior Staff Product Manager to define and lead the go-to-market context graph: the layer that sits on top of our data foundation and Salesforce architecture and gives our go-to-market agents and sellers a shared, continuously learning understanding of how Intuit goes to market.
The context graph has two layers:
•Strategic context. A living model of our GTM strategy: the marketing and sales plays, the segments we serve, our ICPs, and the objectives and constraints we operate under. It continuously absorbs outcome data on what is and isn't working, so the strategy is never a static document. Agents and applications query it to act in line with strategy and adapt as results come in.
•Embedded intelligence. The intelligence built on top of that context: what we know about our customers, the next best actions we derive, and the objectives we want to push, combined with specialized vertical intelligence from third-party providers (for example Gong and Clay) that Intuit could not build alone. Your job is to turn these separate sources into one coherent 'brain' that makes sense for Intuit.
This space is largely undefined today. You will bring it together for the first time, set the charter, and establish the context layer for our go-to-market organization as a platform that every go-to-market domain (prospecting, customer engagement, pipeline and forecasting) builds on. This is an individual-contributor role with enterprise-wide influence. You lead through vision, rigor, and the ability to align many teams, not through reporting lines.
Responsibilities
- Define the vision, strategy, and roadmap for the GTM context graph, the layer that sits on top of our data foundation and Salesforce architecture.
- Build product experiences that make AI-powered features intuitive, transparent, and trustworthy for a diverse range of customers — and bring a clear point of view on where AI genuinely helps vs. where it creates risk
- Design the strategic context model: how plays, segments, ICPs, objectives, and constraints are represented, versioned, and kept current. Sales Ops, Marketing, and BU leaders own the content; you own the mechanism and the standards that make it usable by agents.
- Own the closed-loop feedback system: how outcome data flows back from execution (what worked, what didn't) to update the graph and change agent and seller behavior, with clear measures of whether the loop is working.
- Define the intelligence framework that blends Intuit-built intelligence with third-party provider intelligence, including how signals are combined, arbitrated when they conflict, attributed, and trusted. Identify third-party providers that should be integrated but aren't, and drive that decision.
- Make context available to the consumers who need it: go-to-market agents (including Claude-based and Agentforce agents) and sellers. Define the interfaces, access patterns, and quality bar so that agents can rely on the graph to act.
- Partner with the owners of the data foundation and Salesforce architecture, who own the layers below, to set clear contracts between those layers and the graph.
- Build and continuously refresh a point of view on build vs. buy: when to build in-house, adopt a platform, or partner (for example enterprise graph/context platforms, Data Cloud, or vendor-native capabilities), with explicit trade-offs communicated to engineering and executive stakeholders.
- Define governance for the context layer: ownership, provenance, access, quality metrics, and escalation as new content owners, producers, and consumers are added.
- Translate ambiguous, cross-functional problems into PRDs, evaluation approaches, and phased delivery plans. Prototype and validate with AI tools yourself rather than waiting on handoffs.
- Communicate the vision and progress clearly to executives and frontline stakeholders, and align a broad set of teams around a shared roadmap.
Qualifications
10+ years in product management, with a track record as a senior staff or principal-level PM leading ambiguous, 0-to-1, cross-organizational platform or data/AI products.
• Strong, demonstrated experience operating as an AI-native product manager. You build through AI day to day, and can show real examples of agentic workflows, agents, or AI-enabled products you have designed, built, or shipped.
• Deep understanding of how AI agents consume context: retrieval, knowledge and context graphs, memory, tool use, and evaluation, and a point of view on what makes agent behavior reliable.
• Experience with knowledge graphs, ontologies, semantic layers, or enterprise context/graph platforms, and the judgment to know when each is the right tool.
• Familiarity with the go-to-market domain: sales and marketing motions, segmentation and ICPs, pipeline and revenue lifecycle, and how sales intelligence tools (conversation intelligence, enrichment, signals) are used in practice.
- Experience building closed-loop systems that learn from outcomes, and defining the metrics and experiments that show they work.
- Demonstrated ability to integrate AI tools into your product management workflow to improve quality, speed, or depth.
- Strong data fluency: comfortable working with data models and platforms such as Salesforce, Databricks, or cloud data warehouses, and exploring data yourself with SQL or AI tooling.
- Proven ability to form and defend build vs. buy and platform strategy decisions, and to evaluate vendors critically.
- Exceptional influence and stakeholder management across engineering, data, sales operations, marketing, and executive leadership, without direct authority.
- Bachelor's degree or equivalent experience; Computer Science, MIS, Business, or a related field preferred.
- Enterprise Salesforce experience (Sales Cloud; Data Cloud a plus) is a plus.
- Experience in regulated or high-governance environments where data provenance and access control matter is a plus.
- Prior founding-team or 0-to-1 experience establishing a new platform category inside a larger organization is a plus.
Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits ). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender.
The expected base pay range for this position is:
Mountain View $205,500 - $278,000
San Diego, CA $189,500- $256,000