Senior Product Engineer

Founding Senior Product Engineer

You'll be one of our first engineering hires, working directly with our co-founders to build the product from the ground up — and to shape the architecture, engineering practices, and product direction as we grow.

The work spans a modern AI product: a mobile app police officers use in the field; the AI pipeline that turns voice, photos, and notes into report-ready output; a laptop agent that fills report forms; and infrastructure secure enough for law enforcement data.

This role is for someone who thinks like a founder about the problem, not just the code. You'll take a feature from a vaguely worded feedback to something officers actually use — figuring out what it should do, working with AI tools to build it, and knowing when to loop in customers or the team. You should know your tech well enough to avoid falling off cliffs, but what makes you great at this job is judgment about what to build and why, not just how.

About This Role

• In person, NYC. We work together in the New York City area, with hybrid flexibility. We believe the most effective and fun way to build a company is in a room together.

• In the field. Everyone on the team spends time with customers. Expect some travel to customer sites to watch officers use what you built, then fix what's wrong.

• AI-native. The founding team ships with AI tools every day. We expect the same fluency in your workflow and look forward to learning from you.

Responsibilities

• Take ambiguous, loosely specified problems — a Trello card, a customer complaint, a hunch — and turn them into shipped features, using AI tools to move fast and looping in me or others when it counts.

• Talk to customers directly, in Louisville and beyond, to understand what they actually need — and push back on ideas that sound good but won't hold up in the field.

• Make sound technical calls in service of the product: know enough architecture to avoid foot-guns, without needing to own the system end-to-end.

• Translate business priorities into technical tradeoffs, and vice versa — you're as comfortable in a conversation about revenue or adoption as one about latency or data models.

• Debug and resolve production issues in the features you own.

• Document decisions and communicate tradeoffs clearly to both technical and non-technical audiences.

Qualifications

• Track record of shipping real features end-to-end, from vague requirements to production, with minimal spec.

• Comfortable using AI tools as a core part of building — not just autocomplete, but genuinely building features collaboratively with an LLM.

• Solid technical judgment: you know your stack well enough to avoid costly mistakes, even if you're not the one designing the system architecture.

• Business and user intuition — you can reason about why a feature matters, not just how to build it.

• Strong communication skills across technical and non-technical audiences, including direct customer interaction.

• Comfortable operating independently in ambiguity, while knowing when to ask.

What Success Looks Like

Twelve months in:

• You've shipped a string of features that customers actually use and ask for more of.

• You can take a one-line piece of feedback and turn it into the right thing to build, not just a working thing.

• Customers see you as someone who gets both the tech and their job.

• You've built a reputation as the person who can be handed a fuzzy problem and trusted to figure out the right shape of the solution.

• Leadership spending less time in the weeds of feature decisions because you've got it.