Staff AI Product Manager Jobs in North Carolina

About SpotOn

We’re not just building restaurant tech, we’re giving independent restaurants the tools to compete and win. From our award-winning point-of-sale to AI-powered profit tools, everything we do helps operators boost profit, work smarter, and keep their best people. And every solution is backed by real humans who actually give a sh*t about helping restaurants succeed.

• Named the #1 Restaurant POS by G2 (Fall 2025), based on ratings from real users
• Rated the top-rated point-of-sale (POS) for restaurants, bars, retail, and small businesses by Capterra users
• Awarded Great Places to Work and Built In’s Best Workplaces for multiple years running

We move fast, care hard, and fight for independent restaurant operators to do what they love, and love doing it. If you’re looking to make an impact with heart and hustle, SpotOn is the place for you.

About the Accelerate Team

The Accelerate team is a new 5-person engineering team with a singular mission: prove that AI-native engineering practices can fundamentally change how a fintech engineering org builds software - then make that the new standard. The team has direct VP sponsorship, mission & charter, and three defined projects with hard deadlines.

We're hiring a Staff/Principal IC who has already demonstrated AI-assisted engineering at scale. This is not an "AI-curious" role. You write code with AI every day. You've built agents that do real work. You have strong, experience-backed opinions on which models to use for what, where agents fail, and how to build guardrails that actually hold. You've seen what works in production and you're impatient to do it at scale.

You will be the most technically senior AI practitioner on this team - the person everyone looks to for "how do we actually build this." You don't manage the team. You drive the architecture, build the hardest parts, and set the technical standard.

The Role: Technical Lead, Not Manager

This isn't a "set up some CI/CD and plug in Copilot" role. You are the person who architects the systems that change how SpotOn engineers build software. You will:

Be the AI engineering technical authority. You set the technical standard for how AI is used in code generation, review, testing, and task automation. You don't just implement tools - you design the systems, workflows, and guardrails that make AI-assisted development safe, measurable, and scalable in a PCI-regulated payments environment. The team lead sets priorities; you set the technical direction.

Drive the architecture and implementation of three concurrent projects:

• Automated PR Review - A risk-tiered AI review pipeline where AI handles first-pass review on every PR, with an escalation framework you design that determines when human review is mandatory (payment logic, PCI-scoped code, compliance paths) versus when AI approval is sufficient. You define the criteria. You tune the thresholds. You prove it works.
• Android and API Test Automation - A fully automated test harness for our Android-native POS and KDS products: virtual device provisioning, test execution, teardown, AI-assisted failure analysis - replacing multi-day manual QA cycles with sub-30-minute automated runs.
• AI Agent Swarms - A multi-agent pipeline that takes a PRD and produces a tested, reviewed pull request for tier 1-3 engineering work (nits, bugs, small features). You design the agent orchestration - planner, coder, tester, reviewer - and the blast-radius controls that keep it safe in fintech.

Evangelize by shipping, not by presenting. Your most persuasive argument is a working system, not a slide deck. You demo to engineering leads every two weeks with real metrics. You turn skeptics into adopters by showing them their own time savings.

Measure everything. You define the metrics framework: developer hours recovered, cycle time compression, quality ratios, cost per deployment. You report to the CTO monthly with quantified value delivered. If something isn't working, the data tells you before anyone else.

What We Require

This is a high bar intentionally. We need someone who has already done this, not someone who wants to learn.

Required experience:

• 5+ years building developer tools, infrastructure, or platform engineering systems - you understand how engineering orgs actually work at scale, not just how AI demos work
• 2+ years working deeply with LLMs and AI agents in production - not side projects, not hackathons. Production systems handling real code, real reviews, or real task automation. You can speak to failure modes, cost optimization, prompt engineering patterns, and model selection trade-offs from experience.
• Designed and operated AI-assisted code generation or review systems serving 50+ engineers or 30+ repositories. You know the difference between "cool demo" and "trusted by the team."
• Built multi-agent or agentic workflows - task decomposition, agent specialization, orchestration, error recovery. You've worked with Claude Code, OpenAI Assistants, LangGraph, CrewAI, AutoGen, or custom agent frameworks at a level where you can articulate why you chose one approach over another.
• Hands-on with AI coding tools daily - Claude Code, Cursor, GitHub Copilot, Windsurf, Codeium - you don't just use them, you push their limits. You know where they excel and where they hallucinate. You have a personal workflow that makes you measurably faster and you can teach it.

Required domain expertise (at least two of three):

• Fintech / payments / regulated industry - you understand what PCI-DSS, SOX, or HIPAA compliance means for code review and deployment. You know why "just let the AI merge it" isn't an option for payment logic.
• Mobile / Android testing automation - Espresso, UI Automator, or AI-native tools (Drizz, mabl, testRigor). Experience with emulator farms, device provisioning, and CI-integrated test pipelines.
• Multi-agent system architecture - you've built systems where multiple AI agents collaborate on decomposed tasks with coordination protocols, fallback strategies, and human-in-the-loop checkpoints.

Who You Are

You are not "AI-interested." You are AI-obsessed in the productive sense:

• You already write 50%+ of your code with AI assistance and you've measured the impact on your own velocity. You have opinions on which models are best for which tasks and you update those opinions monthly as the landscape shifts.
• You've built things with agents that most engineers think aren't possible yet. You're 6-12 months ahead of the mainstream in your personal practice and you have the shipped systems to prove it.
• You prototype in hours, not days. You can go from "I have an idea for how to automate X" to a working POC before end of day. You refine ruthlessly after.
• You context-switch across backend, mobile tooling, and AI/ML systems without losing depth. You don't need to be an Android expert, but you need to be dangerous enough to architect the test harness and evaluate the output.
• You communicate technical progress in business terms. You know that "we reduced median PR review time by 47%" lands better with a CTO than "we fine-tuned our prompt chain." You build dashboards, not just systems.
• You're an evangelist, not a gatekeeper. You get energy from showing other engineers how to work with AI. You don't hoard knowledge - you build systems that make the whole org better.
• You have a healthy skepticism forged by real experience. You've seen AI fail in production. You've dealt with hallucinated code, flaky agent workflows, and false-positive reviews. That experience makes your guardrails better, not your enthusiasm less.

What You Won't Be Doing

• Building product features for restaurants (that's the rest of the org)
• Pure ML/AI research without production deployment
• Maintaining legacy systems or writing JIRA tickets all day
• People management - you're a pure IC on a small, senior, fast-moving squad. You write more code than anyone on the team.

Tech Environment

• Languages: Kotlin (Android), Go, TypeScript, Python
• Mobile: Android-native POS applications on dedicated hardware
• Infrastructure: AWS, GitHub, CI/CD (GitHub Actions)
• AI Stack: You'll have significant influence on tool selection - bring your opinions
• Team tooling: Jira, Slack, Figma, standard SpotOn eng stack

We will never ask candidates to pay fees, purchase equipment, or share sensitive personal or financial information during the hiring process. All legitimate communication from our recruiting team will come from an official company email address (@spoton.com). If something seems suspicious, please contact us at careers@spoton.com.

SpotOn is an equal employment opportunity employer. Qualified candidates are considered for employment without regard to race, religion, gender, gender identity, sexual orientation, national origin, age, military or veteran status, disability, or any other characteristic protected by applicable law.

SpotOn is an E-Verify company.

Compensation Range: $210K - $280K