AI receptionist platform built as a full production product for service businesses — handling inbound calls, lead capture, scheduling flows, and customer interactions.
Two-sided digital marketplace — built solo from auth to payments. Live in production with real users.
I design data models that hold up under real usage. 40+ collection Firestore schemas, subcollection chunking for scale, and relationships that make sense.
Live chat, presence, and instant updates using Firestore listeners. I tune real-time features to stay responsive without spiking read costs as usage grows.
Integrated Stripe and crypto payments with retry logic and exponential backoff. I build transaction flows that recover gracefully instead of silently failing.
OAuth, rate limiting, IP-blocking workarounds — I handle the quirks of external APIs so your product stays resilient.
Lazy-loaded images, debounced search, infinite scroll, and caching layers that cut load times without overcomplicating the stack.
Drag-and-drop uploads with client-side resizing and thumbnail generation — keeping storage and bandwidth costs predictable.
Role-based Firestore security rules that give every user exactly the data they're allowed to see — and nothing more.
Firestore transactions and batched writes to keep multi-step operations consistent — even when individual steps fail midway.
Internal dashboards for reports, bans, and flagged content — backed by analytics so moderation decisions aren't made blind.
100% TypeScript codebases with strict mode — catching errors at compile time and shipping zero type-related runtime bugs.
Firebase and AWS services including EC2 for compute, S3 for storage, RDS for relational data, and Lambda for serverless functions.
Unit tests with Jest, integration tests for API endpoints, and E2E tests with Cypress — maintaining 80%+ coverage on critical paths.
Error tracking with Sentry, performance monitoring with Datadog, and structured logging to reduce mean time to resolution.
Algolia integration for fast, typo-tolerant search across large datasets — with faceted filtering and relevance tuning.
PostgreSQL with Prisma ORM for complex queries, reporting, and transactional integrity across relational data.
Schema before code. Every collection and relationship gets mapped out before a single UI component exists — reworking a data model later is expensive.
Identity touches everything — permissions, ownership, security rules. I build it in from day one to avoid retrofitting access control later.
Get the money — or the trade, or the trust mechanic — moving before anything else. This is the part that has to be correct, so I build and stress-test it first.
Chat, presence, live updates — this is what makes a product feel alive instead of static. Layered on top of a working data model and auth system.
Caching, lazy loading, and security rules come last — once the product works end to end, this is what makes it fast and safe to launch.
I'm a full-stack engineer who likes the parts of a build most people avoid: the data model that has to hold up under real usage, the security rules that quietly prevent a breach, the edge case in a payment flow that only shows up in production.
I'm looking for a remote engineering role or contract where I can bring that same ownership to a team's product — someone who can take a feature from idea to shipped without needing much hand-holding in between.
Currently looking for: remote full-stack or backend engineering roles, contract or full-time. I'm available to start.
Send a quick message — I reply within a couple hours.