Senior Software Engineer - Python​/Typescript

About Spot On

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

Our operations, sales, and customer support teams run on workflows that were designed for humans — and many of them should no longer be. Manual handoffs, repetitive processes, slow queues, and duct‑taped integrations are costing us speed, accuracy, and money. We're hiring a Senior AI Engineer to fix that.

Your job is simple to describe and hard to do: find the inefficiencies across our business operations and replace them with AI‑driven systems that are faster, smarter, and scalable. You'll work directly with ops, sales, and support stakeholders, understand their pain points firsthand, and build the automation that eliminates them. One week you might be streamlining a customer support triage workflow;

the next, you're building an agentic pipeline that handles a multi‑step process currently requiring a team of people and days of turnaround.

This is a high‑autonomy, high‑impact IC role. You won't have someone writing detailed specs for you. You'll get a business problem, dig into it, architect a solution, and ship it. We need someone who's been deep in AI‑assisted development for years — not just prompting models, but building real orchestration layers, integrating agentic workflows into production, and producing code that's disciplined and reviewable.

We are not interested in AI‑generated slop.

Own business automation end‑to‑end. You partner directly with operations, sales, and customer support teams to identify workflow bottlenecks and manual processes ripe for automation. You don't wait for a product manager to write you a spec. You discover the problem, scope the solution, build it, deploy it, and measure the impact.

Design and ship AI‑driven systems that replace manual labor. These aren't chatbot wrappers. You're building agentic workflows and orchestration layers that handle complex, multi‑step business processes autonomously — with the guardrails and error handling required for production use in a fintech environment. You build systems that people trust because they work reliably, not because they mandated adoption.

Measure everything. You define the metrics that matter: hours recovered, error rates reduced, cycle times compressed, operational throughput gained. You report impact in business terms. “We automated X and saved Y hours per week” is the language you speak. If something isn't delivering value, the data tells you before anyone else.

Evangelize by shipping, not by presenting. Your most persuasive argument is a working system, not a slide deck. You turn skeptics into believers by showing them their own time savings. You build systems that make the whole ops org better, not just your team.

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

• 7+ years of professional software engineering experience — you understand how engineering and business systems actually work at scale, not just how AI demos work.
• Strong proficiency in Python and Type Script/JavaScript — you can build production systems in both. Not scripts. Not notebooks. Production.
• Full‑stack capability spanning backend services, APIs, and frontend interfaces. You can build the automation pipeline and the dashboard that shows it's working.
• 1–2+ years working deeply with LLMs and AI agents in production — not side projects, not hackathons. Real systems handling real workflows. You can speak to failure modes, cost optimization, prompt engineering…