Product Manager, AI Native Initiatives

At Faros, we are building the engineering intelligence platform for the AI era. We help engineering organizations understand the impact of AI on software delivery while providing the operational context that enables AI agents to operate with greater accuracy, relevance, and trust in complex enterprise environments. Our platform is used by some of the most sophisticated engineering teams in the world, ranging from fast-growing technology companies to F500 enterprises. We believe the future of software development will be built by humans and AI working together, and we're building the foundation that makes that possible.

This is a role for a seasoned, hands-on Product Manager who wants to help define what software development looks like in an AI-native world.

You will own a meaningful surface area of our new AI-native product line. That could mean shaping how engineers collaborate with agents — how they delegate work, provide context, review results, and build trust in what agents produce. It could mean developing the intelligence and evaluation layer that determines whether an agent's work is actually good, and which models, tools, and context produce the best results. Or it could mean connecting these new agentic workflows to the rich engineering context Faros already understands.

These are not mature product categories with established playbooks. The underlying technology is changing quickly, customer expectations are still forming, and many of the most important product questions do not yet have obvious answers. You will form strong hypotheses about where the market is going, collaborate with designers and engineers to turn those hypotheses into working product, put it in front of customers, and learn quickly enough to stay ahead of a rapidly moving field.

We are looking for someone who wants to be deeply in the work: experimenting with new models and tools, prototyping ideas, talking to customers, digging into why an agent succeeded or failed, and developing a strong point of view about what "awesome" should look like. You will have substantial ownership over what we build and a direct hand in creating a new growth engine for Faros.

• Living by our values over avoiding conflict. We favor transparency and honest debate because strong decisions depend on saying the hard things out loud.

• Transformation over predictability. We dedicate our efforts to work that produces monumental outcomes for our customers, even if it means trading short-term predictability for long-term impact.

• Intensity over comfort. We move with urgency and focus, especially when the work is messy or unstructured.

• Craftsmanship over throughput. We take pride in how things are built. Quality, coherence, and care matter. We would rather ship fewer things done right than many things done carelessly.

• Ownership over process. We hand PMs problem spaces, not tasks. We trust them to drive their domain end to end, bring the right people along, and expand what the team is capable of.

• Experience & DNA: 6+ years in product management, ideally with at least 2+ years building AI/ML or LLM-powered products. Startup experience strongly preferred. You have shipped at least one product or major feature from a blank page to real customers, and you can tell that story in detail — including what you would do differently if you ran it back.

• Technical Depth: You have been an engineer at some point in your career, or your product work has been deeply technical enough that engineers respect your architectural instincts. You can read the code, you have opinions on the system design, and you can make the tradeoffs without outsourcing them. Comfortable in technical conversations about API design, system architecture, and prompt engineering. Knowing how to play around with data and draw conclusions is a baseline requirement.

• AI Fluency: Hands-on experience with LLM APIs (OpenAI, Anthropic, or equivalents), embeddings, vector stores, tool use, prompt design, and evaluation. Not just current tool mastery, but persistence, curiosity, and vision. You experiment with AI tools in and outside of work, you do not give up when they fail, and you can articulate where this industry is heading in the next few years and how teams should operate in it.

• Player-Builder Mentality: You do not want just to direct the work; you want to be in it. You prototype. You write. You ship. You dogfood aggressively and dig into the logs to understand why an agent failed. You use modern AI tools aggressively to multiply your own output.

• Opinionated with an Open Mind: You hold strong product convictions and will push back on a Head of Product, a customer, or a head of engineering when you think they are wrong. You also take "you are wrong" with curiosity, not defensiveness or submission.

• Outcome-Driven Mindset: You understand that great products drive business. You will be measured not just on shipping, but on customer satisfaction (CSAT), engagement, and our ability to convert design partners and prospects into successful, closed deals.

• Hacker Spirit: You love solving puzzles. You are happier with a hard, ambiguous problem than a clean, well-scoped one. You poke at edges, ask uncomfortable questions, and would rather find problems yourself than have them find you. You get restless when the work gets too comfortable.

• Domain experience in developer tools, engineering productivity, dev infrastructure, coding assistants, or agent platforms.

• You have shipped a product at a Series A or Series B startup, not just in a large company.

• You have worked on products where humans and AI agents collaborate on the same work, and you have a point of view on what that should feel like.

• You have seriously experimented with modern AI-native tools (Cursor, Claude Code, Codex, Devin, v0, Replit Agent, or equivalents) and have opinions on where each of them wins and loses.

• You have built and run eval frameworks for an agentic or LLM-powered product in production — and have war stories about what broke when models changed under you.

• CS degree or equivalent engineering background.
  

• Location: San Mateo, CA (Seattle considered in exceptional cases)

• Location Type: Hybrid (with in-office attendance three days a week)