Architect the Future of Quality as our next AI Software Development Engineer in Test!
Are you a quality champion ready to build something from the ground up?
Trimble is looking for a foundational AI SDET in Mexicali to establish a brand-new QA team, working alongside our AI development engineers to build a next‐generation API ecosystem and define the state‐of‐the‐art in AI product testing.
What Makes This Role Great
This is a high‐impact, foundational role where you will help establish a brand-new Quality Assurance team in Mexicali.
You will have the unique opportunity to integrate cutting‐edge AI coding assistants and LLM evaluation libraries into the SDLC, moving beyond traditional QA to pioneer testing techniques for the next generation of AI‐driven API ecosystems.
Key Exciting Responsibilities
Partner directly with AI development engineers to build and validate a next‐generation API ecosystem using state‐of‐the‐art testing techniques.
Implement and maintain sophisticated automation frameworks using Playwright, Selenium, and API testing tools to ensure high‐velocity delivery.
Evangelize new automation techniques and best practices, mentoring the growing QA team on AI‐assisted development and prompt engineering.
Design and execute complex performance, regression, and functional test plans to support critical business decisions through data‐driven metrics.
Evaluate and recommend emerging test automation and performance tools to continuously improve software processes and AI integration.
Essential Skills & Experience
Bachelor's degree in Computer Science or a related field with 3+ years of experience in software quality assurance and test automation.
Proficiency in scripting and automation using C#, TypeScript, and/or Python.
Strong foundational knowledge of AI coding assistants (GitHub Copilot, Cursor) and the ethical application of prompt engineering.
Expertise in UI automation (Playwright/Selenium) and API automation frameworks (NUnit, Xunit, or MSTest).
Deep understanding of Agile methodologies and cloud‐based deployment within a CI/CD pipeline environment.
Bonus Points For
Experience evaluating AI models using libraries like Microsoft AI or DeepEval.
Foundational understanding of LLM operations and the ability to configure Model Context Protocol (MCP) servers.
Familiarity with testing microservices and construction project management principles.
Experience in a global work setting with knowledge of performance and security testing tools.
Location: Mexicali, México (office‐based)
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