Senior AI Product Manager

Passionate about food and curious about what drives consumer choices? Join Tastewise and help shape the future of the food and beverage industry.

Tastewise is a human-and-agent food intelligence and marketing platform used by leading companies like PepsiCo, Nestlé, and Kraft Heinz to decide what products to launch, how to market them, and what ultimately makes it to the shelf.

We turn real consumer behavior into actionable insights, helping teams make smarter, faster decisions in a $10 trillion industry that impacts billions of people every day.

If you’re excited about turning data into real-world impact and being part of a collaborative team with a clear mission, this is the place for you!

About the role:

We're looking for a Senior AI Product Manager to take ownership of core areas of our B2B platform - the point where powerful AI capabilities become real products that customers rely on. We've already built the foundation: rich data, agentic infrastructure, and deep domain intelligence. Now we need someone who can take what's working with one customer and make it work everywhere - productizing capabilities, scaling them across our customer base, and raising the quality bar as they grow.

This is a hands-on builder role. You'll work in close, direct partnership with both customers and R&D - running discovery, analyzing the data, and prototyping ideas yourself, then teaming up with R&D to bring them to life at scale.

This is a fast-moving area, and we'll shape the exact scope together, based on where you can create the most leverage for the business. We're looking for true startup reflexes: the ability to shift focus as priorities shift, zero in on what matters most this quarter, and make clear, deliberate trade-offs.

If you thrive in a fast-paced startup environment and want to build AI products that make complex insights accessible and actionable for a real-world, >$1B industry, this role is for you.

What You'll Do

• Own core areas end to end - strategy, discovery, execution, and measurement. Define what success looks like in numbers, and stay accountable to it well beyond launch.
• Productize and scale what works. Turn capabilities proven with one customer into products that work seamlessly across your entire customer base.
• Lead discovery yourself. Run customer and prospect conversations to uncover what people will actually pay for, and bring back a scoped, evidenced bet.
• Prototype your ideas. Go from concept to working prototype using coding agents and AI tooling, with a design bar high enough to serve as a real proposal.
• Own quality. Define what "good" means for our agents, build the evals to measure it, and raise the bar on reliability, cost, and trust as the system evolves.
• Partner deeply with R&D. Engage on technical trade-offs - accuracy, latency, cost, build vs. buy - and earn the team's respect through substance.
• Drive it to market. Team up with design, sales, marketing, and customer success to package, position, and launch it, then feed adoption data back into the roadmap.
  
  

• 4+ years in product, ideally with a mixed background: product plus engineering, or product plus data or analytics. We weigh evidence of what you have built above the number itself.
• AI-native practice. You work fluently with agentic systems and know current best practice: tool and context design, retrieval, orchestration, guardrails, failure modes. You have built and run evals, and you can say where your agents broke and what you did about it.
• Hands-on data fluency. You independently query and interrogate data to size an opportunity, validate a hypothesis, or judge whether an agent's output is any good. SQL and Python or equivalent, used in real work.
• Builder instinct with design judgment. Idea to prototype to product, with coding agents as part of your daily craft. Strong UX orientation for complex data products, and the ability to produce a credible design proposal yourself.
• Customer and commercial range. Comfortable leading discovery calls and working directly with sales and marketing. Excellent communication, with the ability to simplify complexity for customers and executives alike.
• Startup temperament. Proven experience in startups, ideally at scale-up stage. You resolve ambiguity yourself rather than escalating it, and you make trade-offs explicitly.
  
  

• Experience with data-intensive, API or infrastructure-adjacent products where part of the customer is internal.
• Data acquisition experience: sourcing, licensing, partnerships, and the quality and legal questions that come with them.
• Enterprise B2B, especially selling into large CPG, retail or foodservice organizations.
• Food and beverage, CPG or retail domain knowledge.