مهندس برمجيات استخراج البيانات

About Turing:

Turing is one of the world’s fastest-growing AI companies, accelerating the advancement and deployment of powerful AI systems.

Turing helps customers in two ways: Working with the world’s leading AI labs to advance frontier model capabilities in thinking, reasoning, coding, agentic behavior, multimodality, multilinguality, STEM and frontier knowledge; and leveraging that work to build real-world AI systems that solve mission-critical priorities for companies.

Role Overview:

We're staffing a frontier AI data initiative that builds the training data and evaluations used to develop and measure AI agents. You'll join the Mining team, whose job is to turn real-world work into rigorous, long-horizon tasks that AI agents can be trained and tested against.

What you'll do:

• Mine real data, tools, and workflows to understand how knowledge work actually gets done across enterprise applications.
• Author long-horizon agent tasks grounded in that research, realistic, multi-step objectives that mirror genuine digital work.
• Write clear evaluation rubrics that define what correct, complete, and high-quality completion looks like.
• Validate task quality, realism, and correctness through rigorous QA, catching ambiguity, unrealistic assumptions, and grading gaps before tasks ship.
• Work closely with the connectors team, engineers who build Python backends that faithfully replicate SaaS tools (Slack, Linear, Jira, Notion, Gmail, wikis, and similar), to ground your tasks in realistic environments.

What we're looking for:

• Strong backend software engineering, primarily in Python.
• Working knowledge of GCP, Docker, virtual machines, and Harbor.
• Sound engineering judgment and a high bar for correctness, you find edge cases and ambiguity others miss.
• Ability to reason about real-world workflows and translate them into precise, well-scoped tasks and rubrics.
• Excellent written communication; rubric and QA writing is core to the role.
• High daily proficiency with AI coding tools (e.g., Claude Code, Cursor, Copilot), a hard requirement, not a nice-to-have.

Nice to have:

• Experience building or evaluating agentic/LLM systems.
• Familiarity with the SaaS tools above at an API/data-model level.
• Background in data annotation, evaluation design, or QA at scale.
• Candidates may specialize in mining, but the strongest profiles are excellent generalist backend engineers who can also contribute on the connectors side when needed.
• Review long-horizon agent tasks authored by the mining team for realism, correctness, and scope, catching flawed assumptions, ambiguity, and missing edge cases before tasks ship.
• Pressure-test rubrics: confirm they define completion precisely, grade consistently, and can't be gamed or misread.
• Validate tasks end-to-end against the connector environments they run in, verifying that stated objectives are actually achievable and that expected outcomes hold.
• Reproduce and debug failures, then feed clear, specific findings back to task authors and connector engineers.
• Define and improve QC standards, checklists, and processes as the initiative scales.

Offer Details:

• Commitments Required: At least 6 hours per day and minimum 40 hours per week with overlap of 6 hours with PST.
• Employment type : Contractor assignment (no medical/paid leave)
• Duration of contract : 5 week [expected start date is next week]
• Location : India, Pakistan, Nigeria, Kenya, Egypt, Ghana, Bangladesh, Turkey, Mexico