Software Engineer – AI Data Infrastructure

About the role

We are building a frontier AI data initiative that needs strong software engineers to create the infrastructure and training data for AI agents. The role focuses on developing Python‑based backend services that replicate popular SaaS tools and enable large‑scale data collection and task generation.

Key responsibilities

• Build Python backend applications that emulate SaaS tools (Slack, Linear, Jira, Notion, Gmail, wikis) including integrations and full‑service backend functionality.
• Perform thorough backend testing and integration validation to ensure connectors faithfully replicate target systems.
• Adapt, extend, and test existing connectors; develop new connectors from scratch within delivery timelines.
• Conduct data and task mining to identify representative workflows for long‑horizon AI tasks.
• Author realistic tasks derived from mined data, verify task and data quality, and create evaluation rubrics.
• Use AI coding assistants throughout development, QA, and validation.
• Collaborate across connector and task tracks, participate in onboarding, calibration, and quality‑review cycles, and deliver work on schedule.

Required profile

• Minimum 3+ years of professional software engineering experience.
• Strong proficiency in Python with experience in FastAPI, Flask, or Django.
• Proficiency with Git, Docker, and setting up basic software pipelines.
• Experience building scalable backend applications, REST APIs, and microservices.
• Comfortable using AI coding assistants (e.g., Codex, Claude Code, Cursor, GitHub Copilot) in daily workflows.
• Strong analytical and problem‑solving skills with attention to detail.
• Ability to work independently while collaborating effectively within distributed teams.
• Excellent written and verbal communication skills.

Required skills

• Python
• FastAPI
• Flask
• Django
• Git
• Docker
• REST APIs
• Microservices
• AI coding assistants (e.g., Codex, Claude Code, Cursor, GitHub Copilot)