Senior Engineering Manager, Applied AI at GlossGenius in NYC

Job description

About Genius AI Genius AI is building technology to help local businesses run themselves. Genius AI products do the admin work that keeps practitioners from the work they love and the people they serve. From GlossGenius to Reception, its products work 24/7 on busywork like booking, marketing, client management, finances, staff and inventory management, and more. Genius AI technology has saved businesses 106M in admin hours, earned them $2.0B in additional revenue, and facilitated more than 624M client touch points. About the role AI isn’t a strategic initiative for us; it’s how we work. Our bar is transformation, not adoption. The Applied AI team is an internal accelerator: a small pod of forward-deployed builders who find the work where AI changes the outcome, build it with the team that owns that work, and hand it off once it runs. We work on three fronts: Across the business (our primary focus). We embed with areas such as Sales, Marketing and Operations to rebuild how they work. We've shipped an outbound engine our GTM team runs on, and a paid-social insights platform with an embedded agent. The agent helped marketing find inefficient campaign spend that had been hiding in the data and the creative. Next up is the top of our funnel: taking an agentic approach to helping sales and marketing learn which messages, creative and channels actually work. At the frontier. New models, open-weight alternatives, generative UI and agent platforms, tested against real work, so we know what's possible before we need it. You will be the team's first engineering manager, and a builder first. Expect a real share of your week to be hands on: prototyping, pairing on agent architecture and evals, and building the thing yourself when that's the fastest way to make the point. You must be commutable to our NYC headquarters or San Francisco office. We default to being in-office 3–4 days per week, with required attendance on Tuesdays and Thursdays. What you'll do Build, and lead builders. Manage and grow a lean team of engineers, and set the bar for what a fully AI-native engineering team looks like. Drive measurable go-to-market outcomes (pipeline, demos, and closed-won revenue). Partnering across Engineering, Sales, Marketing, Finance, Legal, and People to ruthlessly prioritize a company-aligned backlog—anchoring every initiative to pre-agreed metrics and executive-trusted readouts. Run a tight engagement loop. Intake, one-week sprints with Friday demos, and a clean handoff at the end: a partner team that owns what was built, and a durable owner so Applied AI stays on the next problem instead of carrying the pager. Make evals a practice. Help drive us toward best-in-class here, and share learnings so that every AI product team has a measurable quality bar that lets them move fast safely. Route to the right model. Frontier models first for new use cases; cheaper or open-weight models once a use case is mature and well understood. Push the ways of working forward. Partner with DevEx on experiments that change how engineering works, and turn the ones that work into shared standards, docs and talks, so the whole company gets better at working with AI. What we're looking for You've personally built and shipped agentic systems with real users in the last 12 months. Not evaluated or piloted: shipped. Be ready to walk us through one (or a side project): the architecture, what failed, what it cost, and how you knew it worked. You can tell us how you'd measureAI effectiveness. "Everyone has a license" isn't an answer. We want your opinion on the metric, and on what it would get wrong. You'd rather grow output than headcount. You've changed how you and your engineers work because of AI, and raised your expectations of the team to match. You've managed engineers and still build. 7+ years of software engineering, including 2+ years managing, on a team small enough that you stayed in the code. A scrappy generalist with cross-functional instincts. You've sat i