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AI Summary

Design and maintain scalable automated testing suites for UI, API, and database layers while integrating them into CI/CD pipelines. Collaborate with DevOps teams to ensure test execution within containerized environments and maintain high standards for data integrity.

Join as a Software Engineer to build AI full-stack solutions and shape an engineering culture that values autonomy, creativity, and technical excellence. 🚀

🌟 What do we offer? 

  • A central role in the team that defines the next products, not just maintains the existing ones

  • End-to-end ownership of the agentic AI layer on top of what Labs ships

  • AI-assisted development as a first-class practice, Claude Code, Cursor, Copilot, with the autonomy to exercise real engineering judgment

  • Modern, multi-cloud stack: MongoDB + SQL, Azure + AWS

  • Real influence over architecture, technical standards, and engineering culture beyond your immediate team

  • A high-bar technical environment where your architectural decisions impact multiple teams and products

🧑🏻‍💻 Responsibilities: 

  • Automated Framework Development: Design, build, and maintain scalable automated testing suites for UI, API, and database layers from scratch.

  • Build Hardening & Release Management: Integrate automated tests into CI/CD pipelines to validate builds, detect regressions early, and ensure seamless deployment readiness.

  • UI & Visual Snapshot Testing: Implement automated visual regression and UI testing using modern frameworks (Playwright or Selenium).

  • API & Data Validation: Execute comprehensive API automation and perform complex data comparisons directly against MongoDB and SQL databases to ensure end-to-end data integrity.

  • BDD Implementation: Write and maintain automated acceptance tests using Behavior-Driven Development (BDD) methodologies.

  • Infrastructure & Pipeline Integration: Collaborate with platform/DevOps teams to run automated test suites within Kubernetes and Terraform containerized environments.

🤝 If you have:

  • Experience: 4+ years of dedicated experience as a QA Automation Engineer or SDET.

  • 100% Automation Focus: Proven track record in pure automation; this role does not involve manual exploratory testing.

  • Core Development Stack: Strong proficiency in .NET / C# for writing clean, maintainable test code.

  • Automation Tools: Advanced hands-on experience with either Playwright (including UI snapshots/visual regression testing) OR Selenium.

  • API Testing: Demonstrated experience in API Automation (REST APIs, JSON payloads, contract testing).

  • Database Automation: Hands-on experience querying and validating non-relational databases, specifically MongoDB (data comparison, state verification), alongside SQL Server.

  • Frameworks & Methodologies: Practical experience with Behavior-Driven Development (BDD) frameworks (e.g., SpecFlow, Cucumber, Gherkin).

  • CI/CD & Cloud Infrastructure: Exposure to containerized and infrastructure-as-code environments, including Kubernetes, Terraform, and continuous integration pipelines (GitHub Actions, Azure DevOps, etc.).

🦾 Core Stack Summary

  • Working familiarity with Model Context Protocol (MCP), agent frameworks, and eval frameworks

  • Experience deploying inference workloads on Azure (AI Foundry / Azure OpenAI) and/or AWS (Bedrock, SageMaker)

  • Experience with Autodesk products and APIs (AutoCAD, Revit, Fabrication, BIM 360 Docs, Forge / APS)

  • Construction, MEP, or manufacturing domain knowledge

  • Experience leading large-scale system migrations or architectural transformations

  • Familiarity with modern serverless technologies on either cloud

  • Track record of establishing technical standards across engineering organizations

  • Understanding of event-driven architectures and message-based integration

This call is made within the framework of Law 19.691 on the Promotion of Employment for Persons with Disabilities, including individuals registered in the National Registry of Persons with Disabilities of the Ministry of Social Development

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