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Senior Software Engineer - Agent Evaluation - Freelance/Remote 100+ openings

Braintrust

full-remoteseniorfreelancebackend United States Today via LinkedIn

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Tags

AI agent evaluationPythonFastAPIReactTypeScriptDockerPostgreSQLKafkaIntegration TestingEnglish B2+

About the role

Role Overview

You’ll contribute to building a dataset used to evaluate AI coding agents—measuring how well a model handles real-world developer tasks. Work is project-based (not permanent employment).

Responsibilities

  • Build realistic developer environments: create a simulated “virtual company” with a codebase, infrastructure, and context (tickets, docs, conversations).
  • Design evaluation tasks from intermediate states: craft prompts, define what it means for the agent to be successful, and ensure tasks are solvable by an AI agent.
  • Write tests to verify solutions: accept all valid approaches and correctly reject incorrect ones (balanced strictness).
  • Iterate with QA feedback: review agent solutions, analyze failures, and refine tasks/tests to make evaluations fair and robust.

What This Is NOT

  • Not data labeling
  • Not prompt engineering
  • Not writing code from scratch (the agent writes most of the code; you guide and evaluate)

Requirements

  • 5+ years software development experience
  • Core stack experience: Python (FastAPI), JavaScript/TypeScript (React), Docker, PostgreSQL, Kafka, Redis
  • Experience writing functional and integration tests
  • English proficiency: B2+

Nice-to-haves / Additional Expectations

  • Ability to complete identity verification and a technical assessment
  • Willingness to use Discord for communication and updates
  • Reliable internet and effective communication in a remote setting

Logistics

  • Estimated effort: ~20 hours per task (varies by complexity)
  • You choose when/how to work, but tasks have deadlines and must meet acceptance criteria.

About Braintrust

Braintrust is a talent network connecting specialists to project-based opportunities with leading technology companies. The work described here focuses on evaluating and improving AI coding agents by building realistic test datasets.

Scraped 7/27/2026