Founding Engineer
Building scalable MVPs from zero to one.
Need a founding engineer to build your MVP? Sharon Rosario brings zero-to-one product experience — database architecture, backend, frontend, and deployment — and has been the first engineer building production SaaS at getconch.ai and ilumiera.ai.
Delivering scalable, intelligent solutions by integrating full-stack development, automation, AI/ML, and cloud—engineered with modern technologies and a focus on architectural excellence. Read the Git worm incident write-up, the multi-tenant RAG architecture, or the About page.
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Founding Engineer — overview
A founding engineer is not just a senior developer who joined early. It is the person who turns a founder's idea into a running product, makes the architecture decisions that either compound or haunt the company for years, and sets the engineering culture before there is a team to inherit it. Sharon Rosario has done exactly this as a founding engineer at getconch.ai and ilumiera.ai.
The zero-to-one job is about sequencing: what to build now, what to fake, and what to defer without painting the codebase into a corner. Sharon optimizes for shipping a real product to real users quickly, while keeping the data model and service boundaries clean enough that scaling later is a matter of investment, not a rewrite.
The decisions that matter at zero-to-one
Data model first: the schema is the hardest thing to change later, so it gets designed carefully even when everything else is a prototype. Auth, billing, and multi-tenancy are treated as foundations, not bolt-ons, because retrofitting tenant isolation into a live product is painful and risky.
Everything else — internal tooling, admin panels, edge cases — is built just enough to unblock the next milestone, and revisited only when usage proves it needs to be real.
From prototype to production
Sharon builds the MVP to be demoable in weeks, then hardens the parts that face load: moving blocking AI calls to background queues, adding observability, and setting up CI/CD so shipping stays fast as the surface area grows. The two case studies below are concrete examples of that hardening work.
Related case studies
Zero-Leak Multi-Tenant RAG Architecture
Building a B2B AI product where one customer can never read another customer's data — using Postgres Row-Level Security and pgvector.
Read the case studyDecoupling AI: From Blocking Calls to Event-Driven Microservices
Moving from fragile synchronous OpenAI calls to a scalable pipeline with Node.js, FastAPI, BullMQ, Redis, and WebSocket streaming.
Read the case studyFrequently asked questions
A founding engineer owns architecture, sets up the initial stack and deployment, makes the trade-off calls on what to build versus defer, and establishes engineering practices — all before there is a team. They are accountable for the product working in production, not just for completing assigned tickets.
A demoable MVP typically takes a few weeks depending on scope, with auth, billing, and the core data model built as real foundations rather than throwaway prototypes so the product can be hardened for production without a rewrite.
Yes — Sharon is a founding engineer at getconch.ai and ilumiera.ai, building production AI SaaS from zero to one across the full stack.
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