Short Term Contract (2-3 weeks) - Might extend based on need

About the Role

We are staffing a frontier AI data initiative that requires robust software engineers to build the infrastructure and training data used to develop and evaluate AI agents.

Key Responsibilities:

- The Engineer will, depending on assigned track: build Python backend applications that replicate existing SaaS tools (such as Slack, Linear, Jira, Notion, Gmail, and wikis), including implementing integrations and standing up full-service backend functionality;

- Perform thorough backend testing and integration validation to ensure each connector behaves faithfully like the system it emulates;

- Adapt and extend previously built connectors as needed, and test existing connectors internally before they are treated as complete; Build new connectors from scratch where required, within agreed delivery timeframes;

- Conduct data mining and task mining to identify representative workflows suitable for long-horizon task development; Author realistic tasks derived from mined data and workflows;

- Verify task and data quality, realism, and correctness through structured QA; Write clear evaluation rubrics that define correct, partially correct, and deficient work;

- Use AI coding agents proficiently throughout all development, QA,



and validation work; collaborate across the connectors and tasks tracks,

- Participate in onboarding, calibration, and quality-review cycles; deliver assigned work to the expected quality bar and on agreed milestones.

Must Have Required Skills:

- Minimum 3+ years of overall experience

- Strong proficiency in Python (FastAPI, Flask, or Django)with proven experience in backend software development.

- Proficiency with Git, Docker, and basic software pipeline setup.

- Experience building scalable backend applications, REST APIs, and microservices.

- Proficiency in using AI coding assistants (e.g., Codex, Claude Code, Cursor, GitHub Copilot, or similar) as part of daily development workflows.

- Strong understanding of software engineering best practices, including version control, testing, and code quality.

- Strong analytical and problem-solving skills with attention to detail.

- Ability to work independently while collaborating effectively within distributed engineering teams.

- Excellent written and verbal communication skills.

Nice to have:

- Experience building connectors or integrations for SaaS platforms.

- Knowledge of evaluation frameworks, QA methodologies, and rubric creation for AI datasets.

- Experience developing realistic workflows for long-horizon AI tasks.

📌 Python Docker Engineer (India)
🏢 Turing
📍 India