Principal Product Manager

Active Intelligence is already live — autonomous agents serving 180,000+ businesses, with real traction and a roadmap that gets more ambitious with every release. What we need now is the product leader who accelerates the layer that makes all of it smarter.

This is a principal-level IC role focused on two connected problem spaces: the context intelligence layer that gives Active Intelligence its depth, and the deep reasoning agent that turns that depth into marketing insight no other platform can deliver. You’ll work alongside our Head of Applied AI, Head of Active Intelligence Engineering, and a team of product leaders who are each driving pieces of the autonomous marketing vision. Your piece is arguably the most leveraged — because everything else in the platform gets better when context and reasoning get better.

We ship fast, iterate in days not quarters, and expect product managers to own outcomes end-to-end — from prototype to production to in-market adoption. If you’re looking for a role where scope is handed to you and success is defined for you, this isn’t it. If you want to define both, keep reading.

Partner with Applied AI Teams to Build the Context Layer. Define and ship the structured intelligence layer that gives Active Intelligence deep understanding of each customer’s business — their goals, brand, audience behavior, campaign history, and what’s actually working. This is the signal architecture that turns 20+ years of marketing data into something every agent on the platform can reason over. You lead how context matures, what signals matter, and how it compounds across the product.

Build the Deep Reasoning Agent. Leverage frontier model capabilities — extended thinking, multi-step research, cross-source synthesis — to create a marketing intelligence agent that actually thinks about what’s happening. Not dashboard summaries. Deep analysis: why engagement shifted, what top-performing segments share, where the next campaign should focus and why. You define what “deep” means in a marketing context and ship something that makes static reporting feel obsolete.

Connect the flywheel. The reasoning agent without context is a wrapper. The context layer without a flagship consumer is infrastructure. You own the loop where deeper context produces more powerful reasoning, which drives more engagement, which generates richer context.

Own quality and evaluation. Design the eval frameworks — golden sets, quality rubrics, output grading — that determine whether the reasoning agent is actually good, not just impressive in a demo. You set the bar for what “marketing-grade intelligence” means and build the measurement systems to hold it.

Operate as a technically credible builder. You prototype with frontier models directly, test prompt architectures, and challenge engineering on system design — not because you want to do their job, but because the best product decisions at this layer require that depth. You’re credible enough to pair with applied AI and ML engineers as a peer, and you have the product judgment to know when technical elegance is serving the customer and when it’s not.

• Exceptional product taste grounded in technical depth. You combine sharp instincts for what makes an experience genuinely useful with the technical credibility to engage deeply on system architecture, data models, and model behavior. Former engineering experience or an equivalent technical foundation is a strong signal.
• Eval-driven quality mindset. You know that shipping AI features is easy and shipping reliable AI features is the actual job. You’ve designed evaluation frameworks, defined quality bars, and built the feedback loops that separate demo-ware from production intelligence.
• Customer value over technical elegance. You instinctively ask “what does this unlock for the marketer?” first. You’ve seen infrastructure projects lose their way and you know how to keep shipping things that matter.
• Ownership mentality that doesn’t wait for permission. You operate with founder-level drive — you see the gap, you build the prototype, you make the case, you ship it. Your growth here is defined by your own ambition and the impact you create, not by a ladder or a process. We’re building something that hasn’t existed before, and the people who thrive here are the ones who treat that as an invitation, not an obstacle.
• First-principles thinking in ambiguous domains. These problem spaces don’t have playbooks to copy. You define categories, not follow them.
• Cross-functional gravity. You move people without positional authority — because the thinking is sharp, the framing is right, and the judgment is trusted. You work at the intersection of data/ML, the agent platform, and the broader product org.

• Significant product management experience, with meaningful time building AI/ML-powered products in production at scale — not proofs of concept, production systems serving real users.
• Direct experience shaping data platforms, context systems, or structured intelligence layers — you’ve made consequential decisions about what data to capture, how to structure it, and how to make it useful.
• Track record of defining new product capabilities in fast-moving, ambiguous domains where you couldn’t copy someone else’s playbook.
• Production experience with frontier AI models and agentic architectures — you’ve learned the hard way what works in production versus in a demo.
• Marketing technology or customer engagement platform experience is a strong advantage — you understand the domain deeply enough to have real opinions about what marketers need.

Active Intelligence is real, it’s growing, and the roadmap ahead is the most ambitious product vision in marketing technology. You’re joining at the moment where the foundation is proven and the next layer of intelligence is what separates us from everyone else.

What this unlocks for you: You get to define the context and reasoning architecture for an AI platform that 180,000+ businesses already rely on — not a startup pitch, a live product with real customers and real signal. You’ll work with frontier models on problems where marketing domain expertise and AI product craft intersect in ways that don’t exist at horizontal AI companies. And you’ll have the autonomy and speed of a team that treats principal ICs as the primary unit of product leadership — not a layer of management with review gates above you.

This is the role that makes the autonomous marketing vision compound.