Quality Assurance AI Engineer

Quality Assurance Engineer - Cybersecurity & AI (SF Bay Area)

Are you the kind of person who breaks things to understand them—then builds stronger testing frameworks from what you've learned? We're developing the next generation of AI-powered cybersecurity analytics and looking for a Quality Assurance Engineer to help us push the boundaries of security testing, data validation, threat detection verification, and more! You'll work at the intersection of AI, cybersecurity, data analytics, and your own deep curiosity for quality.

About Us

We're a well-funded AI startup ($25M seed round) in the San Francisco Bay Area, led by serial entrepreneurs with decades of success in cybersecurity and data analytics (achieving > $3B valuations). We have paying customers and are partnering with Fortune 500 companies on a mission to transform the cybersecurity landscape with cutting-edge AI, including AI agents and Generative AI.

Why This Role Matters

As one of our first Quality Assurance Engineers, you'll shape how modern AI-driven cybersecurity systems validate threats, analyze data, and perform at scale. Your work will ensure that our threat detection models, security analytics, and automated defense systems operate with precision and reliability. From validating threat intelligence pipelines to ensuring our security AI operates flawlessly in real time, your testing strategies will power defenses that operate at machine speed—so our customers can trust their security posture.

What You'll Do

• Design & Execute Security-Focused Test Strategies: Develop and implement comprehensive testing strategies for our cybersecurity analytics platform, including functional, integration, regression, performance, and security testing. Validate threat detection accuracy, false positive rates, and incident response workflows.
• Build & Maintain Test Automation for Security Systems: Create robust, scalable test automation frameworks for security analytics, threat detection pipelines, and AI-powered security agents. Implement CI/CD pipelines that catch vulnerabilities and quality issues before they reach production.
• Validate Threat Detection & Analytics Accuracy: Design and execute validation tests for threat intelligence data, security event processing, and analytics outputs. Verify that our AI models correctly identify threats, vulnerabilities, and anomalies across diverse attack scenarios and security contexts.
• Test AI/ML Security Models: Develop specialized testing approaches for AI-driven cybersecurity features, including model accuracy validation, adversarial testing, bias detection, and output verification. Ensure our security AI agents perform reliably against real-world attack patterns.
• Data Pipeline & ETL Testing: Validate the integrity, accuracy, and timeliness of security data pipelines processing logs, alerts, and threat intelligence from multiple sources. Test data transformations, aggregations, and enrichment processes for security analytics.
• Performance & Scale Testing: Conduct performance testing for high-volume security event processing. Validate system behavior under attack scenarios, load spikes, and large-scale data ingestion to ensure reliability during critical security incidents.
• Security & Vulnerability Testing: Perform security testing on the platform itself, including API security, authentication/authorization, data encryption, and secure data handling. Identify and validate fixes for security vulnerabilities in collaboration with the security team.
• Partner with Cross-Functional Teams: Collaborate with security researchers, data engineers, ML engineers, and product teams to understand threat scenarios, security requirements, and edge cases. Integrate quality checks throughout the development lifecycle.
• Produce Actionable Quality Metrics: Create detailed test reports, security quality dashboards, and documentation that provide clear visibility into product health, detection accuracy, and system reliability. Track defect trends and security issue patterns to drive continuous improvement.
• Champion Security Quality Culture: Mentor team members on security testing best practices, advocate for quality-first development in cybersecurity products, and establish testing standards that scale as the team grows.

What We're Looking For

-5-7 years minimum of hands-on experience in quality assurance, test automation, or software testing, preferably in cybersecurity, security analytics, or related domains

- Experience testing security products (SIEM, XDR, TVM, threat intelligence platforms, or security analytics tools)

- Strong programming skills in Python, Java, or similar languages for test automation

- Experience with test automation frameworks, CI/CD pipelines, and testing methodologies (e.g., Pytest, Selenium, TestNG, Jenkins)

- Knowledge of cybersecurity concepts: threat detection, vulnerability management, security events, attack patterns, and security frameworks (MITRE ATT&CK, NIST, etc.)

- Experience testing REST APIs, microservices, and distributed systems

- Strong SQL skills and experience with database testing, data validation tools (e.g., Great Expectations), and ETL testing

- Understanding of data pipeline architectures and security data processing

- Familiarity with security testing tools (Burp Suite, OWASP ZAP) and secure coding practices

- Bonus: Experience with AI/ML testing, security research, threat intelligence, or building testing systems that scale with high-volume security data

Why Join Us?

- Early-stage impact with the stability of $25M in seed funding

- World-class leadership across AI, Cybersecurity, Engineering, and Product

- Traction with Fortune 500s already in motion

- Highly competitive comp & equity

- Health, wellness, and professional development benefits

- Access to the latest tools in AI/ML and cybersecurity development

Work Location – San Jose, CA (5 days in the office, founding team)