CertifyOS is an API-first platform with an increasingly complex product surface. As we scale more integrations, more enterprise customers, more AI-powered workflows the application layer has to evolve without accumulating the kind of technical debt that kills product velocity.
How do you build a frontend that scales with product complexity without becoming unmaintainable? React and TypeScript at the component level is straightforward. At Staff level the problem is harder: design systems, state management strategy, API contract alignment between frontend and backend, and a component architecture that lets a growing team move fast without stepping on each other.
How do you design API contracts that serve both internal product teams and external enterprise consumers? CertifyOS APIs are external-facing products, not just internal plumbing. You’ll define versioning strategy, resource modeling, error semantics, and pagination patterns that work for enterprise integrations with complex compliance requirements and evolve without breaking existing consumers.
How do you deliver a polished enterprise product experience on top of complex, async data workflows? Provider credentialing and enrollment are long-running, multi-step processes. You’ll architect the application patterns optimistic UI, async job tracking, real-time status updates via WebSockets or SSE that make these workflows feel fast and reliable to end users even when the underlying operations aren’t.
How do you keep application performance and reliability high as the data layer grows? As our Spanner and BigQuery footprint scales, the application layer is where query latency, pagination strategy, and caching architecture either absorb or amplify that complexity. You’ll own the performance boundary between the data layer and the product.
How do you integrate AI capabilities into the product without compromising UX or reliability? We’re building AI-powered workflows into the platform agents, LLM-assisted credentialing, intelligent data surfacing. You’ll define how those capabilities integrate into the application layer: latency handling, fallback behavior, streaming UX patterns, and eval instrumentation that surfaces quality issues in production.