Python & AI Developers
A Python developer who has actually shipped AI features to production, not just experimented in a notebook: retrieval pipelines, model integration, evaluation, and the unglamorous data plumbing underneath. Embedded in your team, hourly or full-time.
AI experience is easy to claim and hard to verify
Every resume now lists an AI project, but there is a real gap between a weekend notebook and a production system with rate limits, cost controls, and a fallback for when a model gets something wrong. Hiring badly here means paying to relearn the hard lessons about grounding, evaluation, and cost that a developer who has already shipped this work would bring from day one.
What they actually do
- Build retrieval and grounding pipelines so a model answers from your real data, not just its training
- Integrate LLM APIs with rate limits, cost caps, and a defined fallback for failures
- Write production Python services and APIs, not just scripts and notebooks
- Build and maintain data pipelines that feed a model or a reporting system reliably
- Set up evaluation so you can tell whether a change actually improved output quality
- Work within your existing infrastructure and monitoring rather than a separate one
How it works
- 1
Scope the role
We confirm whether the need is core Python backend work, AI integration, or a mix, and what stack it runs on.
- 2
Match a developer
You get developers with real, shipped AI or Python backend work, verified against what they actually built, not just listed on a resume.
- 3
Trial period
A short, paid trial on a real piece of work, often a specific integration or pipeline, before a longer commitment.
- 4
Embed with your team
The developer works in your repo and your model or data infrastructure, hourly for a defined scope or full-time as an ongoing hire.
- 5
Stay supported
A senior engineer reviews cost, safety, and architecture decisions on anything touching a model in production.
What you get out of it
- AI features that reach production with cost and failure modes actually handled
- Python backend capacity that does not need to relearn the basics of shipping software
- A trial period that separates real experience from a resume line
- Senior oversight on the decisions that get expensive to get wrong later
Questions we get about this
Yes, most are comfortable across the major hosted APIs and open-source model runtimes. We confirm the specific provider and any private or self-hosted requirements during scoping.
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Ready to scope python & ai developers?
Send us the details of your setup: the tools, the volume, the workflow. We'll come back with an honest assessment and a fixed quote.