Role Description
This is not a traditional Product Manager role. We are not looking for someone who writes requirements and waits for engineering. We are looking for someone who builds.
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You will take a workflow from concept to working prototype before a sprint starts.
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You will design AI systems, not just describe them.
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You will validate with real users, not decks.
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You will own the full arc from insight to production, including the parts that used to belong to other functions.
If that sounds like the job you have been trying to do inside a traditional Product Manager role, this is the upgrade.
What You Will Actually Do
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Prototype before planning.
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Design AI workflows end-to-end.
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Own the evaluation layer.
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Reason about cost and latency.
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Validate with users, not stakeholders.
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Ship. Not someday. Fast.
Qualifications
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4+ years in a product role, with at least 2 years working directly on AI-powered products.
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Demonstrated ability to build working prototypes using AI development tools (Claude Code, Cursor, v0, or equivalent).
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Hands-on experience designing agentic workflows, including tool use, memory, and multi-step reasoning.
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Clear understanding of RAG, prompt architecture, and when to use models versus rules.
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Experience defining and running evals for AI features in production.
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Track record of shipping products, not just planning them.
Strong Signal
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You have built something on your own, outside of a job, using AI tools.
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You can walk through the cost and latency tradeoffs of a feature you shipped.
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You have worked in a paired product-engineering model where prototypes precede specs.
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You have owned a feature from zero to production, including the parts no one assigned to you.
Not Required
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Computer science degree.
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Ability to write production-ready backend code.
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Experience at a large company (small team instincts are a plus here).
What You Will Not Do
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Write long PRDs that sit in Notion waiting for an engineering sprint.
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Coordinate meetings between functions that should be talking directly.
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Manage backlogs in isolation from the users they are supposed to serve.
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Treat AI as a feature category rather than a design medium.
How We Work
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We eliminated traditional PRDs. Product and engineering work in paired ownership, with prototypes expected within hours of a new idea.
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Reviews are outcome-based, not output-based.
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The expectation is that you can move fast enough that engineering is validating something real, not waiting for a handoff.
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This is a high-trust, high-accountability model.
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You will have significant autonomy over what you build and how you build it.
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You will also be expected to show your work, early and often, in the form of working artifacts, not status updates.
How to Apply
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Skip the cover letter. Instead, send us:
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One example of a prototype or working artifact you built using AI tools. A link, a demo, a repo, anything real.
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Two to three sentences on the workflow it automated or the problem it solved.
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The cost or latency tradeoff you had to navigate to make it work in practice, even if it was just for a side project.
We will respond to every submission that includes all three.
Benefits
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A global, connected team.
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Be part of an AI Native Organization.
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Innovating a $100 Billion industry.
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Join the rocketship to scale-up 10x and beyond together.
Smartcat Culture Code
At Smartcat, we are committed to building a culture that highlights respect and appreciation for each individual's unique background and perspective, while maintaining a strong focus on results and engagement. We believe in welcoming everyone and fostering an inclusive environment where team members can be their authentic selves at work. Our commitment to inclusion is steadfast, and we stand firmly against discrimination and harassment.