At KMS Technology, we are dedicated to delivering cutting-edge solutions and services that empower businesses to achieve their goals. Our team is composed of highly skilled professionals who are passionate about technology and innovation. We provide a dynamic and collaborative work environment where you can grow your career and make a significant impact.

We're looking for a highly skilled Senior Automation Engineer to join our Quality Assurance team, focusing on high-integrity software solutions for complex automation and Computer Vision systems. This critical role requires a strong background in defining and executing both manual and automated test strategies across software and hardware interactions. The ideal candidate will have direct familiarity with the NVIDIA Computer Vision ecosystem, including DeepStream frameworks, GPU architecture, and understanding storage solutions like Trident, enabling the creation of robust tests for real-time video processing and derived data accuracy.

Responsibilities:

Automation Strategy & Execution

• Design, develop, and maintain the end-to-end automation framework using industry-standard tools (e.g., C#, Python, Selenium/Playwright) to ensure comprehensive test coverage for backend services and UI components.

• Translate complex system requirements, user stories, and hardware specifications into clear, executable, and maintainable automated test cases and detailed manual test protocols.

• Lead the integration of automated tests into the CI/CD pipeline, focusing on continuous testing to ensure zero regression in production deployments.

• Manage and triage defects identified through automation runs, working closely with development to ensure timely and effective resolution.

  Computer Vision and Hardware Quality

• Familiarity with NVIDIA DeepStream and its pipeline components to design tests that validate the integrity and accuracy of real-time video processing, metadata extraction, and inferencing results.

• Develop specialized tests to validate the performance and reliability of software executing on NVIDIA GPUs, including load testing and verifying resource utilization.

• Understand the role of storage management solutions like NVIDIA Trident in containerized environments (Kubernetes) and create tests to ensure data persistence and availability for vision models and results.

• Execute necessary manual and exploratory testing on integrated hardware/software devices to cover scenarios (e.g., physical failure modes, user interaction, complex environment shifts) that are impractical to automate.

  Quality Leadership & Process Discipline

• Act as the quality gatekeeper for key releases, ensuring all testing activities adhere to established standards and methodologies (e.g., Agile, SCRUM, or regulated frameworks if applicable).

• Mentor and guide junior QA resources on advanced automation techniques, test architecture best practices, and the integration of specialized hardware testing.

• Drive continuous improvement by proposing and implementing new tools, processes, and metrics to increase the efficiency and coverage of the QA lifecycle.

Required Experience & Technical Skills

• Minimum of 5+ years of professional experience in Software Quality Assurance and Test Engineering.

• 3+ years of direct experience developing and maintaining automated test frameworks using languages such as C#, Python, or Java.

• Expert proficiency in translating complex functional requirements into comprehensive test plans and test cases (both manual and automated).

• Proven experience with API testing (e.g., Postman, RestAssured) and performance testing tools.

• Strong working knowledge of Continuous Integration/Continuous Delivery (CI/CD) pipelines and tools (e.g., Jenkins, GitLab CI, GitHub Actions).

Preferred Skills & Domain Knowledge (Highly Desired)

• Direct experience testing systems leveraging real-time Computer Vision or image/video processing.

• Familiarity with the NVIDIA DeepStream SDK, or similar vision processing pipelines, and understanding how data integrity must be validated within these specialized streams.

• Basic understanding of NVIDIA GPU architecture and its role in accelerating applications.

• Experience with container technologies (Docker, Kubernetes) and persistent storage orchestration (e.g., NVIDIA Trident or similar volume managers).

Location: Guadalajara, Jalisco, Mexico (working from home - office won't be mandatory all the time, rather it will required from time to time).