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Hire FastAPI & Python AI Developers

Async Python 3.12+ and FastAPI microservices engineered for low-latency AI streaming, Pydantic v2 type safety, and high-concurrency APIs.
15 SaaS & AI products in live production. 500+ ventures supported since 2005. Retained ~150-specialist bench.

The Default Backend Backbone for Production AI & Data Platforms

FastAPI has become the undisputed standard for modern AI orchestration and data-intensive SaaS backends because it unites Python's native machine-learning ecosystem with Rust-backed Pydantic v2 validation, asynchronous ASGI concurrency, and auto-generated OpenAPI 3.1 contracts. Yet naive FastAPI codebases routinely stall in production when synchronous CPU or ORM calls block the asyncio event loop under concurrent streaming load.

Eternitech deploys senior FastAPI and Python engineers who understand async I/O boundaries, SQLAlchemy 2.0 async connection pooling, Server-Sent Events (SSE) token streaming, and distributed Celery / Dramatiq task queues—overseen by veteran startup operators in Miami and Tel Aviv.

Core FastAPI Engineering Capabilities

  • Low-Latency Streaming AI & WebSocket Gateways: Non-blocking SSE and WebSocket endpoints streaming LLM tokens, tool status updates, and real-time telemetry directly to Next.js and mobile clients.
  • Strict Pydantic v2 & OpenAPI Contracts: End-to-end schema validation generating typed TypeScript SDKs automatically so frontend and backend contracts never drift.
  • Async PostgreSQL, pgvector & Worker Pipelines: Tuned asyncpg / SQLAlchemy 2.0 repositories paired with PgBouncer, Redis rate limiters, and durable background workers for heavy document ingestion.
  • Production Observability & Container Hardening: Multi-stage Docker builds, Uvicorn/Gunicorn tuning, OpenTelemetry tracing, and ninety-percent-plus pytest async test coverage.

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Seamless Integration With Existing Node.js, PHP, or .NET Stacks

Many Series A and enterprise teams keep their core transactional monolith in Node.js, Laravel, or .NET while introducing a dedicated FastAPI AI sidecar for RAG, embeddings, and agent orchestration. Our operators design clean internal mTLS/JWT boundaries so your new Python AI tier plugs into existing auth and billing without friction.

Frequently Asked Questions

When should we choose FastAPI over Django or Node.js?

FastAPI excels when you need high-concurrency async I/O, streaming LLM/agent endpoints, strict OpenAPI/Pydantic contracts, and direct access to Python AI/data libraries without Django's monolithic ORM overhead.

How do your engineers prevent event-loop blocking in FastAPI?

We enforce strict async database/HTTP drivers on hot request paths, offload CPU-bound PDF parsing or local reranking to dedicated worker pools, and run automated load tests before production launch.

Can we hire a combined FastAPI + Next.js full-stack pod?

Yes—Next.js on the edge/frontend paired with FastAPI + PostgreSQL pgvector on the backend is our single most requested Dedicated Engineering Pod configuration in 2026.

Still comparing FastAPI teams?

Skip the pitch. Get a real scope breakdown first.

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Tell us what you're building.

No pitch deck required. Just a description of what you need. We'll come back with a scope breakdown — and we'll be honest if we're not the right fit.

⚡️Scope & architectural analysis in roughly 60 seconds.