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Senior, zero-to-one. Own the architecture; the data model is your contract.
San Francisco Bay Area Hybrid, in-person by default Senior Meaningful founding equity + salary
Make collaboration work between people, machines, and AI.
Twenty years ago organizations coordinated people. Today they coordinate people and software. Tomorrow they will coordinate people, AI agents, machines, and humanoids. Nothing in the modern stack was built for that. Organizations do not fail because people lack intelligence; they fail because that intelligence is not coordinated, and coordination failures already cost the economy roughly $2 trillion a year.
Ignizia is building the operating layer for human-AI-machine coordination. This is the unsolved layer of the AI transition: independent research keeps finding that capable AI agents lose much of their capability the moment they have to work together, and that the hardest problems in enterprise AI are organizational, not technical. Coordination cannot be downloaded. It has to be captured and shaped from how a real organization actually works, and whoever holds that teaming-context layer holds something no one else can import.
So we start at ground zero: small and mid-size manufacturing, the most coordination-dependent, least digitized work there is. We are live with a design partner, a 60-person luxury footwear manufacturer, where the platform is being shaped view by view against real operations. We are founder-led, early stage, and hiring our founding team.
You will not be starting from a blank page. Ignizia already has an unusually complete product definition: a 33-view interactive product canvas simulating the platform 30 days into a live pilot, a canonical naming and information-architecture brief, established navigation and accessibility patterns, and an engineering-grade relational data model. The founder holds the product vision and has set the frame.
Alongside the canvas sits a full relational data model written as an engineering contract: design laws, roughly 29 entities, a provenance spine (source, confidence, fidelity level, consent scope, validation dates), and explicit privacy rules. That document is your contract. You own how it becomes a real system. And it is not just a schema: it is the teaming-context layer itself, the system of record for how a real organization coordinates. If the thesis is right, what you build here is the foundation everything else stands on.
We will walk the data model together and ask where it breaks: which entities are underspecified, which constraints are expensive, what you would build first and why. Expect a working session, not a whiteboard puzzle.