Software Engineer, Python & Docker (LatAm & Mexico)

Urgent hire: LatAm and Mexico only. ASAP start, 2 to 4 week contract. Applications are reviewed on a rolling basis, so apply early.

Engagement details

• Engagement type: contractor, pay per task.
• Payment: $300 per approved task.
• Commitment: minimum of 1 completed and approved task per day.
• No cap on tasks: complete as many as you can until the pipeline is exhausted.
• Duration: 4 weeks, starting immediately.

About Turing & the role

Turing is one of the world's leading AGI infrastructure companies, working with frontier AI labs to accelerate model development through high-quality training data, evaluations, and engineering talent. We are staffing a frontier AI data initiative building the infrastructure and training data used to develop and evaluate AI agents. You will be assigned to one of two tracks: connectors or tasks.

Responsibilities

• Use AI coding agents throughout development, QA, and validation.
• Participate in onboarding, calibration, and quality reviews, delivering to the quality bar on agreed milestones.

Connectors track

• Build Python backend applications that replicate existing SaaS tools (Slack, Linear, Jira, Notion, Gmail, wikis).
• Test and validate connectors so each behaves faithfully like the system it emulates, and extend existing connectors and build new ones within agreed timeframes.

Task track

• Mine data and workflows to identify candidates for long-horizon task development, and author realistic tasks from them.
• Verify task quality, realism, and correctness through structured QA, and write evaluation rubrics defining correct, partially correct, and deficient work.

Requirements

• 3+ years of backend development experience with strong Python (FastAPI, Flask, or Django).
• 3+ years with Git, Docker, and pipeline basics, with solid testing and code-quality practices.
• Experience building scalable backends, REST APIs, and microservices.
• Daily use of AI coding assistants (Claude Code, Codex, Cursor, GitHub Copilot, or similar).