Associate Product Manager

Rockstar•San Francisco, CA

2d•$110,000 - $150,000•Hybrid

About The Position

Rockstar is recruiting for an AI voice agent company that is the market leader for mortgage lenders. Founded in 2024, they've grown like crazy (~$0 → $13M in 20 months), and currently count 5 of the 10 largest independent mortgage banks in the U.S. as enterprise customers. They raised $21M across their Seed and Series A from top investors. The market pull is exhilarating — the company has grown 10× in the past 12 months and more than 100× since its seed round, all without a dedicated sales or marketing team. The company is a high-agency team where the bar is high and everyone makes the people around them better. Collaboration and intensity are core team values: people truly care about their work and their coworkers. At the same time, the company doesn't take itself too seriously. Outperforming human sales teams on half a million daily calls is not easy. Low-latency, real-time infra. 99.9% uptime. Enterprise-grade privacy and security. Advanced simulation and evaluation systems. Flexible A/B testing. AI scheduler and dialer. The company owns the whole stack without compromising quality. The company raised $21M+ in total funding, most recently a $15M Series A in June 2026.

Requirements

This can be your first product role.
How you think and write matters more than your last job or relevant experience.
An unusually strong writer. You'll write to customers, draft instructions that agents run on, and document what you learn. Clear writing is most of this job.
Judgment about what matters. You'll always have more requests than time, and you'll need to decide which is which.
Comfort with ambiguity and speed. You'll get dropped into unfamiliar issues and be expected to figure them out.
Real curiosity about AI. You don't need to have built agents before, but you should want to badly.

Responsibilities

Directing AI agents to build AI agents.
Standing up new voice agents, reworking existing ones, and extending the internal systems that assemble and maintain the whole fleet.
Owning the voice agents for some of the largest mortgage lenders in the country — talking to them directly, learning what their loan officers actually do all day, and turning that into an agent that performs.
Starting on changes to existing agents and building new ones end to end within a few months.
Growing into the hardest use cases — pulling credit, recommending loan products — first alongside Product Managers, then running them yourself.
Owning the agents for a set of the company's largest lenders: Their requests come to you, and you own both the work and the relationship — from a same-day adjustment to a complete rebuild of how an agent handles an entire conversation.
Building new agents, end to end: Take a customer's messy real-world process, decide how it should work as a voice conversation, and build it.
Identifying pattern recognition across customers: See every request that comes in and identify when multiple requests are really one missing feature, pushing that into the roadmap instead of building it repeatedly.
Setting the quality bar for your agents: You decide when something is good enough to go live on real calls, and what isn't worth building at all.