Hire SaaS Developer for Startup Who’s Shipped It Before

When you hire a SaaS developer for a startup, the first two weeks decide most of what follows, so I spend them on things that are expensive to change later rather than on features. I map the domain into a clean data model, draw the tenancy boundary, and stand up a walking skeleton that is deployed to a real environment on day one. My default stack is TypeScript end to end, usually Next.js with a typed API layer, Postgres as the single source of truth, Prisma or Drizzle for migrations, and background jobs on a proper queue. Boring, well-understood tools beat clever ones here; a startup needs velocity and the ability to hire around the codebase, not a resume of exotic frameworks.

The decisions that matter most are rarely visible in a demo. I keep everything in a modular monolith until there is a measured reason to split it, because premature microservices are the quickest way to burn a seed round. For tenant data I weigh Postgres row-level security against a schema-per-tenant layout against a plain tenant_id on every row, and I pick based on your compliance posture and expected tenant count, not on fashion. Stripe webhooks are made idempotent from the start, money flows are reconciled against the database rather than trusted blindly, and every external call that can fail is retried with back-off. These are the choices a junior or an offshore shop quietly gets wrong, and they surface as outages once you have paying users.

Good, to me, is measurable and it is boring in the right places. Every change ships through CI with type-checking, a focused test suite, and automatic migrations, so you can deploy several times a day without ceremony. I instrument the product with structured logging, error tracking such as Sentry, and a handful of real metrics so you can see activation, latency, and failed payments instead of guessing. I write tests where bugs are costly, namely billing, permissions, and tenant isolation, and I do not chase a coverage number for its own sake. Feature flags let us ship half-finished work safely and run the pricing and onboarding experiments that actually move retention. The aim is a codebase a new hire can read on their first morning.

Most of my value is in the mistakes I prevent or quietly undo. I replace hand-rolled authentication with a vetted provider, because a bespoke password reset flow is a breach waiting to happen. I add database migrations and seed scripts to projects that were editing schemas by hand in production. I fix N+1 queries and missing indexes before they become a 3am incident, enforce tenant_id at the query layer so one customer can never read another's data, and make webhook handlers idempotent so a Stripe retry does not double-charge anyone. I also push back on scope: the fastest way to miss a launch is to build the admin panel, the mobile app, and the integrations marketplace before a single customer has paid you anything.