QA Automation Engineer

Verkada is transforming how organizations protect their people and places with an integrated, privacy-sensitive AI-powered platform that includes solutions for video security, access control, air quality sensors, alarms, intercoms, and visitor management.

We’ve got serious momentum in the market: more than 30,000 customers (including 100+ of the Fortune 500), a $5.8B valuation, more than $1 billion in annualized bookings, and backing from CapitalG, Sequoia Capital, General Catalyst, Felicis Ventures, Next47 and more. Physical AI is one of the most consequential technology shifts of our time, and Verkada is at the center of it.

You can look at all kinds of communities to see our platform’s impact in the world. It's the retailer that uses our agentic AI to deter theft before it happens. The warehouse that uses AI-powered alerts to make sure its team is protected on the floor with proper PPE. The school that’s alerted to a threat in real-time and triggers a lockdown in seconds, not minutes. We’re rapidly scaling this impact: today, more than 2 million Verkada devices are deployed across 170+ countries.

We're focused on hiring engineers who understand not only the device and embedded systems, but also how they perform and evolve at scale in the field. You’ll work across the full device lifecycle—from developing automated HIL and regression tests and validating new features, to analyzing fleet telemetry, monitoring releases, and investigating issues reported by customers. You’ll collaborate closely with embedded, backend, hardware, and other QA automation engineers to improve test coverage, release quality, and the reliability of devices deployed in the field. If you’re looking for a fast-paced environment where your work directly improves the quality and reliability of products shipped to customers, this is the place for you!

• Developing tools to analyze fleet health, actively monitoring devices after releases, creating alerts, and managing device configurations in the field

• Working with large volumes of data (Querybook, Grafana, AWS Athena)

• Monitoring telemetry data from devices in the field

• Analyzing automated HIL regression test results, running automated tests on release builds and performing a few remaining manual checks

• Developing proofs-of-concept to validate how the remaining manual tests and new features can be automated, then implementing automated tests and adding them to the regression suite

• Expanding regression test coverage based on fleet health analysis and customer-reported bugs

What You Bring

• 5+ years of experience in software QA, release engineering, or testing physical/embedded devices

• Experience designing test strategies and developing automated test cases, with a focus on regression and end-to-end testing

• Good knowledge of Python, CI/CD, Linux, networking, and databases

• Understanding of hardware/software interactions and the ability to troubleshoot issues on physical devices

• Experience automating manual QA processes, including developing proofs-of-concept and turning them into reliable regression tests

• Ability to identify, reproduce, investigate, and clearly report issues found during automated testing or fleet monitoring

• Experience with release validation and fleet health monitoring

• Experience with configuration and release management

• Grafana or similar tools to visualize telemetry data

• BDD methodology (Gherkin syntax)

• TeamCity, GitHub Actions

• Embedded systems, device