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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Music supervisors searching for sync licensing tracks have two problems: too many options and too little time. Searching a catalog of 800,000 tracks b...
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Business dashboards are reactive by design — you open them when you think something is wrong. Predictive alerting flips that: the system tells you som...
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GDPR compliance is mostly an engineering problem dressed as a legal one. The right to erasure, data portability, consent management, and purpose limit...
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Enterprise sales is driven by signals — a prospect company just raised a Series B, a competitor's customer published a negative review, a key champion...
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Live sports commentary that sounds like a human analyst wrote it — contextually aware, statistically grounded, emotionally appropriate for the moment,...
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You can't know how a new model will behave in production until it's in production — unless you have a shadow testing framework. Shadow mode runs candi...
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Nobody writes good documentation. Not because engineers don't know how — they do — but because documentation is always the lowest priority and the fir...
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Support teams spend 45 minutes per ticket searching through documentation that should take 90 seconds to find. We've built a conversational knowledge...
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A distributed trace with 3,000 spans is technically observable but practically unreadable. On-call engineers staring at a waterfall of spans during an...
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Our AI creative platform helps marketing teams produce ad copy, product descriptions, email subject lines, and social content at scale. The platform h...
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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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