Software Engineer - Python + Docker
About The Role:
Vraify is seeking experienced software engineers for a short-term remote initiative focused on realistic backend systems, integrations, and long-horizon AI tasks. You will build production-minded Python services, test connector behavior, and help create reliable technical evaluation workflows. This is an independent contractor role paid per approved task. The project is expected to run for 2-3 weeks, with the possibility of extension based on project needs. Contributors should be able to complete and receive approval for at least one task per day.
What you'll do:
- Build Python backend applications that replicate SaaS tools such as Slack, Linear, Jira, Notion, Gmail, and wikis.
- Implement complete backend functionality, integrations, REST APIs, and connector workflows.
- Test backends and integrations to ensure connectors behave accurately and reliably.
- Extend existing connectors or build new connectors from scratch.
- Mine data and workflows to identify representative long-horizon tasks.
- Write realistic technical tasks and clear evaluation rubrics.
- Verify task and data quality through structured quality assurance.
- Use AI coding agents throughout development, testing, and validation.
- Participate in onboarding, calibration, and quality-review cycles.
- What we look for
- At least 3 years of professional software engineering experience.
- Strong Python backend development skills using FastAPI, Flask, or Django.
- Experience with Git, Docker, REST APIs, microservices, and basic software delivery pipelines.
- Daily proficiency with AI coding assistants such as Codex, Claude Code, Cursor, GitHub Copilot, or similar tools.
- A strong grasp of testing, version control, code quality, and software engineering best practices.
- Strong analytical, problem-solving, and communication skills.
- Ability to work independently and collaborate effectively with distributed teams.
- A LinkedIn profile included in your resume.
Nice to have:
Experience building SaaS connectors or integrations.
Knowledge of evaluation frameworks, quality-assurance methods, or rubric creation for AI datasets.
Experience developing realistic workflows for long-horizon AI tasks.
Experience with Claude or Claude Code.