Senior Engineering Manager, Applied AI

Genius AI; San Francisco (CA); Hybrid; USD 240,000 - 300,000; Full time

Job summary

Genius AI is seeking an engineering leader in San Francisco to build and guide a lean, AI-native engineering team. You will prototype and ship agentic systems used by real users, while aligning engineering work with business outcomes such as pipeline, revenue, and time saved.

You’ll collaborate across Sales, Marketing, and Operations, and help define processes that scale with AI-driven product teams, ensuring fast, measureable impact while maintaining high-quality standards.

Qualifications

• You’ve personally built and shipped agentic systems with real users in the last 12 months.
• You can tell us how you measure whether a team is using AI well and what it would miss.
• You’d rather grow output than headcount and have raised the team’s expectations to match.

Responsibilities

• Build and lead a lean team of engineers, setting the bar for an AI-native engineering team.
• Drive go-to-market outcomes and provide readouts executives trust with clear metrics.
• Run an efficient engagement loop: intake, one-week sprints, and durable handoffs to partner teams.

Skills

Agentic systems

Engineering management

Software engineering

Cross-functional instincts

Metrics aligned with business outcomes

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 accelerant: 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. That last step matters. We keep moving at AI speed by handing off what's stable and taking on the next hard problem, not by maintaining everything we've ever built.

We Work On Three Fronts

• Across the business (our primary focus). We embed with 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, and iterate on them in days, not weeks.
• Inside engineering. Engineering speed is still our biggest lever. Our DevEx team owns Geni, our in- house background coding agent. Applied AI partners with them to test what comes next (new agentic patterns, self-maintaining tools, pipelines where agents ship and humans approve) and helps them push new ideas to scale.
• 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’ll be the team’s first engineering manager, and a builder first. Expect a real share of your week to be your own hands in the work: 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.
• Move business numbers. Drive go-to-market outcomes (outbound replies, demos, closed-won deals, top-of-funnel leads), with a metric agreed at the start of every engagement and a readout executives trust.
• 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.
• Say no well. Work with leaders across Engineering, Sales, Marketing, Finance, Legal and People to find the highest-leverage opportunities, and keep a stack-ranked backlog tied to company priorities.

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 measure whether a team is using AI well. "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 inside a sales, marketing or operations team's workflow, understood it, and helped them adopt something new.
• You tie engineering work to business outcomes like pipeline, revenue, time saved or cost avoided, and report on them clearly.
• You’re comfortable building the process where there isn’t one, and only as much process as the team needs.

What This Job Is Not

• It isn’t "the AI team" that lets everyone else stop owning AI. Part of the job is pushing capabilities back out.
• It isn’t a platform org. The team has a clear mission based on impact, and we believe in the power of lean, AI-first teams to move mountains.
• It isn’t pure research. We’re not afraid to try something crazy and throw it away, but our goal is to find ways to ship impact.

At Genius AI, we celebrate our differences and are committed to creating a workplace where all employees feel supported and empowered to do their best work.

We believe this benefits not only our employees but our product, customers, and community as well.

Genius AI is proud to be an Equal Opportunity and Affimative Action Employer.

Personal Information: Notice at Collection for Employees and Applicants

Agency Submissions

If a resume or applicant is submitted to Genius AI by a third party without a signed search agreement in place, it will become the property of Genius AI and no fee will be paid, irrespective of whether the candidate is hired.

Genius AI may use automated tools, including artificial intelligence and machine learning systems (AI Tools), to assist in evaluating applicants’ qualifications and fitness for the position. These AI Tools may be used alongside human review during one or more stages of the recruiting process, including application screening, skills assessments, and interviewing. No final hiring decision will be made solely by AI Tools without human oversight.

Compensation Range: $240K - $300K