Next.js & FastAPI Full-Stack Developer
React frontends with high-performance Python backends.
Hire Sharon Rosario, a Next.js and FastAPI developer building fast React frontends backed by high-performance Python APIs — a proven pairing for AI products and data-heavy SaaS.
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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Next.js & FastAPI Full-Stack Developer — overview
Next.js on the frontend and FastAPI on the backend is one of the most effective pairings for modern products: React's ecosystem and rendering flexibility, with Python's data and AI libraries behind a fast, typed API. Sharon Rosario builds full-stack products on exactly this combination.
FastAPI's async model and Pydantic typing make it a natural fit for AI workloads and data-heavy endpoints, while Next.js delivers a fast, SEO-friendly frontend. Sharon connects the two with typed contracts, streaming where it helps, and a Postgres data layer designed for correctness under real load.
Why this pairing works
FastAPI gives you async request handling, automatic OpenAPI docs, and Pydantic validation — ideal for serving AI models and data endpoints. Next.js gives you server rendering, routing, and a first-class React developer experience for the UI.
Sharon keeps the boundary between them clean: typed API contracts, sensible error handling, and streaming responses for long-running or AI-generated content so the frontend stays responsive.
The data and infra layer
Postgres as the source of truth (with pgvector when retrieval is involved), Redis and background workers for anything slow, and Docker-based deployments on Vercel, AWS, or GCP. The event-driven case study below shows a FastAPI service working as part of a larger streaming pipeline.
Related case studies
Decoupling 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 studyZero-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 studyFrequently asked questions
Next.js provides a fast, SEO-friendly React frontend with server rendering, while FastAPI provides an async, typed Python backend that excels at AI and data workloads. Together they cover modern full-stack needs without compromising on either side.
Yes — its async model handles slow model calls well, Pydantic gives you strong request/response validation, and it integrates directly with Python's AI and data libraries. Sharon pairs it with background queues so long AI calls never block requests.
Postgres as the primary store, with pgvector for retrieval-augmented generation, and Redis for caching and background job queues.
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