Lead Product Manager - Dialpad

About Dialpad Dialpad is the AI-native business communications platform. We unify calling, messaging, meetings, and contact center on a single platform - powered by AI that understands every conversation in real time.

More than 70,000 companies around the globe, including WeWork, Asana, NASDAQ, AAA Insurance, COMPASS Realty, Uber, Randstad, and Tractor Supply, rely on Dialpad to build stronger customer connections using real-time, AI-driven insights.

We’re now leading the shift to Agentic AI: intelligent agents that don’t just analyze conversations but take action by automating workflows, resolving customer issues, and accelerating revenue in real time. Our DAART initiative (Dialpad Agentic AI in Real Time) is redefining what a communications platform can do.

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Being a Dialer At Dialpad, AI isn’t just a feature; it’s how our teams do their best work every day. We put powerful AI tools in every employee’s hands so they can move faster, think bigger, and achieve more.

We believe every conversation matters. And we’ve built the platform that turns those conversations into insight and action, for our customers and ourselves.

We look for people who are intensely curious and hold themselves to a high bar. Our ambition is significant, and achieving it requires a team that operates at the highest level. We seek individuals who embody our core traits:
Scrappy, Curious, Optimistic, Persistent, and Empathetic .

Your role Our AI organization builds, runs, and hosts the models behind our products: custom SLMs, our ASR stack, and the inference infrastructure that serves them in real time. Products like our voice agents and agentic runtime are joint efforts with product engineering — but the models they run on are built here, and this role owns product for exactly that layer.

It's a different job from the rest of platform and product engineering: research-driven, eval-heavy, and closer to training data and model behavior than to sprint boards. The standard PM toolkit doesn't cover it. The day-to-day runs on eval reports, latency budgets, and knowing whether a failure is a model problem, a serving problem, or a prompt problem — and without that fluency, even an excellent PM ends up coordinating from the outside instead of deciding from the inside.

This is not a role you can do at the API-orchestration level. You need to know how models are built and run, ideally because you've built them.

We're hiring someone who won't have that problem. You've been on the other side of the table — as an AI researcher, applied scientist, or ML/AI engineer — and you've since moved into product, or you're ready to. You don't need a translator between you and the people building the system, and they don't need one between them and you.

• Own product direction across the full model lifecycle — data, training and adaptation, evaluation, release, production m