Python Developer for AI Prototype (LLM + State Comparison, Short Project)

Remote, USA Full-time Posted 2026-05-31
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Python Developer for AI Prototype (LLM + State Comparison, Short Project)

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Description

I’m looking for a developer to help build a lightweight AI prototype using OpenAI or Anthropic APIs.

This is NOT a full product build.

This is a focused prototype to test a specific idea.

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Project Goal

Build a simple Python-based system that:

1.Runs the same LLM task multiple times.

2. Captures outputs and any intermediate state (memory/logs).

3. Compares differences between runs.

4. Classifies differences into simple categories:

o Stable

o Boundary

o Violation

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What This Means

Think:

  • Run the same prompt 5–10 times.
  • Log results.
  • Detect where outputs or stored data differ.
  • Label those differences.

That is it.

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Technical Requirements

Must have:

  • Python
  • Experience with OpenAI API or Anthropic API
  • Ability to build simple, clean scripts (no over-engineering)

Nice to have:

  • LangChain or similar frameworks.
  • Streamlit (for simple UI/dashboard).
  • Experience with logging or comparing outputs.

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Important Constraints

This should be:

  • Lightweight.
  • fast to build.
  • easy to understand.

Please DO NOT:

  • Design complex architectures.
  • build full systems.
  • over-engineer.

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Deliverables

  • Python script or small app.
  • Ability to run repeated LLM tasks.
  • Stored logs of runs (JSON or similar).
  • Basic comparison logic between runs.
  • Simple classification output.

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Timeline

  • 3–7 days initial build
  • Max 1–2 weeks total

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Engagement Style

  • Fixed-price or hourly (open to discussion)
  • Will start with a small paid test task before full project

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Screening Question (Required)

Please answer this:

If you needed to run the same LLM task multiple times and compare outputs/state between runs, how would you build it quickly?

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Who This Is For

Ideal candidate:

  • Builds fast prototypes.
  • Comfortable with LLM APIs.
  • Prefers simple solutions over complex systems.

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Bonus

If this goes well, there may be follow-on work.

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