Hire Dedicated Developers

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.

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Python & AI Developers

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. 1

    Scope the role

    1 day

    We confirm whether the need is core Python backend work, AI integration, or a mix, and what stack it runs on.

  2. 2

    Match a developer

    2–3 days

    You get developers with real, shipped AI or Python backend work, verified against what they actually built, not just listed on a resume.

  3. 3

    Trial period

    3–5 days

    A short, paid trial on a real piece of work, often a specific integration or pipeline, before a longer commitment.

  4. 4

    Embed with your team

    Ongoing

    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. 5

    Stay supported

    Ongoing

    A senior engineer reviews cost, safety, and architecture decisions on anything touching a model in production.

How we work

How we deliver

  1. 1

    Discovery & Scoping

    1-3 days

    We start by understanding the actual problem and your existing systems, not just the brief.

  2. 2

    Architecture & Plan

    2-4 days

    We map the technical approach and integration points before any code gets written.

  3. 3

    Build

    1-8 weeks, scoped to your project

    AI-augmented development that moves fast without skipping review.

  4. 4

    Test & Launch

    2-3 days

    Real testing against real scenarios before it touches a live user.

  5. 5

    Tune & Support

    Ongoing

    We monitor and refine in the weeks after launch. This isn't a handoff and disappear.

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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