Remote positions
Browse vetted remote FastAPI positions — model serving APIs, LLM backend engineering, and production inference systems at companies shipping real AI products.
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Content teams at enterprise companies produce 200+ pieces per month across blogs, social, email, and documentation. The bottleneck isn't writing — it'...
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Our document processing platform handles 2 million receipts per month for expense management companies. The OCR layer works well for standard printed...
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We've built one of the largest enterprise knowledge graphs in the legal sector — 14 million nodes, 89 million edges, covering case law, statutes, and...
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Eighty thousand customer support tickets a month. That's what our clients' teams handle, and our AI assistant already resolves 40% of them automatical...
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Carbon accounting is mandatory for thousands of EU companies, but most don't have the technical infrastructure to measure their emissions accurately....
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Our clients send 5 million LLM API calls per day, and 40% of them share identical system prompts. Without caching, every call reprocesses the same 2,0...
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Public records — permits, court filings, property transfers, business registrations — contain critical information that journalists, researchers, and...
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Our ML platform has a powerful API — and nobody uses it correctly. Engineers copy code from Slack threads, hardcode credentials, skip error handling,...
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When an AI system makes a decision that affects someone's insurance premium, loan application, or medical treatment, regulators want to know exactly h...
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Every international transaction must be screened against sanctions lists — OFAC, EU, UN, and 40 other regulatory bodies. Traditional screening uses fu...
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Role guide
FastAPI has become the default framework for serving AI models and LLM applications in Python, largely because its async support and automatic validation fit naturally with inference workloads. Remote FastAPI jobs at AI companies usually mean building the API layer between a model and the rest of a product — handling streaming responses, request batching, and production reliability, not just wrapping a model in an endpoint.
What remote FastAPI jobs are posted on RemoteAI?
Mostly AI backend and model-serving roles — building the API layer for LLM products, ML inference endpoints, and internal tooling that connects models to the rest of a product. Most require production Python experience beyond basic CRUD APIs.
Why do AI companies prefer FastAPI over Flask or Django?
Native async support handles the I/O-bound nature of model inference and streaming LLM responses well, and built-in Pydantic validation reduces boilerplate for the structured request/response formats AI APIs typically need.
Do FastAPI jobs require ML experience, or just backend skills?
It varies. Some roles are pure backend engineering — you serve models built by others. Others expect you to understand model behavior well enough to design sensible APIs around it (batching, timeouts, streaming). Check individual listings for the split.
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