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# Sr. QA Automation Engineer

- **Company:** Veritone, Inc.
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $140,000.0 - $150,000.0
- **Contract:** Permanent contract
- **Skills:** JavaScript (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Automation of Tests, Cloud Computing, Code Review, Continuous Integration, Software Debugging, Apache JMeter, Load Testing, Scrum Methodology, Regression Testing, TypeScript, Google Cloud, Postman, Cypress (Programming Language), Kubernetes, Playwright, Restful APIs, Programming Languages, Microservices
- **Published:** May 27, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=227b84a39d6305c0

## About the Role

Do you have experience in Regression testing implementation?, alongside engineering partners

- Follow and contribute to QA standards, best practices and coverage criteria established by the team

- Participate in risk-based test planning and prioritization for multi-service features and releases

- Collaborate with developers through code reviews and pairing to promote testability and quality

- Champion quality in sprint planning and design discussions - helping shift testing earlier in the cycle

- Identify gaps in tooling or processes and propose improvements within your team's scope

# **WHAT YOU'LL NEED**

- 3-5 years of QA engineering experience with a strong automation focus

- Hands-on experience with Cypress, Playwright or a comparable modern test automation framework

- Proficiency in at least one programming language - JavaScript/TypeScript strongly preferred

- Working knowledge of REST API testing using tools such as Postman

- Experience running automated test suites in CI/CD environments

- Solid understanding of testing methodologies: unit, integration, end-to-end, regression and exploratory testing

- Good debugging skills and ability to trace failures across web and API layers

### 

### **BONUS POINTS IF**

- Experience with enterprise SaaS or AI/ML-powered products

- Familiarity with performance/load testing tools such as k6 or JMeter

- Exposure to cloud infrastructure or microservices architectures (AWS, GCP, Kubernetes)

- , Experience in regulated or public-sector





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