Senior Product Manager, Thanx

• You go to the customer first and the data second, and you can tell the difference between a loud request and a real pattern. You bring evidence, not anecdotes, and you have opinions you built yourself rather than inherited from a roadmap meeting
• You are hands-on with AI tooling in practice, not in a slide deck. You’ve spent real time in Claude Code, Codex, or comparable agentic tools, built your own prototypes and workflows with them, and you have opinions about where they break. You can read a schema, write a query, follow a pull request, and hold your own with engineers on tradeoffs. You don’t need to be an engineer; you do need to be unafraid of the codebase
• You write well, because our specs are read by humans and agents alike and clear writing is the core craft. You thrive with a broad mandate and little process, and you build conviction with leadership through evidence rather than escalation
• 5+ years of product management, with a track record of shipping products that real customers use and pay for. Ideally B2B SaaS, ideally data-heavy
• Hands-on with AI tooling, in practice, not in a slide deck. Real time in Claude Code, Codex, or comparable agentic tools, including prototypes, scripts, or workflows you built yourself
• Customer-obsessed and evidence-driven. You go to the customer first and the data second, and you can tell a loud request from a real pattern
• Technical fluency. You can read a schema, write a query, follow a pull request, and hold your own with engineers on tradeoffs
• Strong written thinking. Our specs are read by humans and agents alike. Clear, precise writing is the core craft
• High ownership in ambiguity. You thrive with a broad mandate and little process
• Based in the US or Canada. We’re 100% remote, almost entirely in North America

Desirable

• You will own a meaningful area of the next generation of the Thanx platform, end to end, from the customer problem to the shipped product to whether it actually moved the business. This is real product, for real restaurant brands, on real data
• The surface area is wider than “loyalty software” suggests. Thanx today spans:
• Consumer experiences. Branded mobile apps and web ordering used by millions of restaurant guests, each brand distinct on a shared foundation
• Loyalty. Points, tiers, check-in and card-linked programs, redeemable online and in-store
• Marketing automation and CRM. Segmentation (including SegmentAI), campaigns, offers, and A/B testing in a self-serve merchant dashboard
• Data and reporting. Capture rate, Insights Lab, guest identity resolution, and the warehouse underneath it all
• AI products in market. RecoveryAI, which resolves guest issues after an order, SegmentAI, and a merchant-facing MCP server that puts a brand’s Thanx data inside the AI assistant they already use
• Integrations. The POS and ordering systems restaurants actually run on: Toast, Square, NCR Aloha, PAR Brink, Qu, Revel, Olo, and others
• There is a lot of surface area and not many PMs. That means real ownership: the decisions you make change how hundreds of brands run their guest relationships, and the data comes back fast enough to tell you whether you were right
• We are profitable, with industry-leading retention, and we are long past the search for product-market fit. We are rebuilding the platform around AI, and this role is about what that platform becomes next
• Thanx has reorganized around AI. Claude Code is in daily use in every function, and every employee has an unlimited token budget. We didn’t stop at handing people tools. We built the internal systems that turn customer voice into shipped product, and we keep tightening that loop:
• Customer voice is queryable. Sales calls, support conversations, CRM history, app-store reviews, product analytics, and the data warehouse sit behind one internal platform our agents can reason over. “What are our largest brands saying about reporting?” takes minutes to answer, not a quarter of research
• PRDs are living, versioned systems. Our internal, custom-built tooling holds every requirement with its full decision history, what changed, when, and why, alongside live clickable prototypes and the project’s working channel. A requirement set revs a dozen times in a few weeks as customers react to it and engineers build against it
• Prototypes come before tickets. A PM can take a requirement to a working prototype in front of a customer in an hour or less, so we argue about the real thing instead of a mockup
• Agents do real engineering work. Our agent fleet picks up specified features and bugs, opens root-caused, review-ready pull requests, reviews human PRs, and improves its own skills based on how its PRs fared. Engineers stay accountable for everything that merges
• Prioritization runs on signal, not volume. Every initiative carries explicit conviction from CS, sales, marketing, finance, partnerships, product, and data, so the roadmap reflects where the business is actually pulling
• The result is a pace most product orgs haven’t seen yet. The bottleneck has moved. It’s no longer how fast we can write specs or ship code. It’s judgment: picking the right problem, knowing what “good” looks like for a restaurant operator, and noticing when the system is confidently building the wrong thing. That judgment is the job
• You will also help build the machine. The workflows above are young, and the PM who joins now will shape how product is made here, the skills, the agents, the templates, and the guardrails, not just use them
• Own a platform area end to end. Discovery, definition, delivery, and the outcome. You’re accountable for whether it worked, not just whether it shipped
• Live close to customers. Talk to restaurant operators and marketers every week. Mine the call, support, and usage data our tooling puts at your fingertips. Bring evidence, not anecdotes
• Go from signal to prototype to product fast. Turn customer voice into blueprints, blueprints into prototypes customers can react to, and prototypes into shipped product, in cycles measured in days and weeks
• Direct agents, not just people. Write specs precise enough that an agent can build from them, review what comes back, and know when it’s wrong
• Design AI-native product. Many of the problems in front of us, segmentation, issue recovery, campaign guidance, merchant analytics, are being rebuilt with AI at the core. Shape how intelligence shows up in the product, and how merchants come to trust it
• Make data the product. Much of our value to a brand is proving what’s working. You’ll work with order, loyalty, and guest-level data across hundreds of brands, and turn it into decisions merchants can act on
• Improve how we build. Contribute to the internal tooling, skills, and workflows that make the whole product org faster