Sr. Engineer, SDET - AI Detection and Response (AIDR) (Hybrid, Sunnyvale)
$140,000–$215,000 year
HybridSunnyvale, California, United States
Job Summary
Design and implement contract testing frameworks to verify API contracts across browser extensions, API gateways, and cloud platforms. Establish comprehensive test strategies spanning unit, integration, and end-to-end layers while modernizing test infrastructure for AI security controls. Develop testing patterns for AI-powered detection capabilities and model efficacy, creating metrics dashboards and alerting through observability. Work with SRE and developers to create playbooks and support documentation for multi-collector deployments and policy enforcement workflows. Onboard rapidly to contribute meaningfully within the first 60 days to a fast-paced engineering environment.
Required Qualifications
- 10+ years combined software development and test automation experience
- proven track record of establishing quality frameworks
- delivering reliable, scalable test coverage for enterprise-grade cloud SaaS products at scale
- Experience building testing frameworks and tooling for Cloud SaaS products
- Strong computer science fundamentals (algorithms, data structures, distributed systems)
- Expertise at programming languages: Python, Go, Javascript
- Deep understanding of: Cloud architectures and microservices
- Web Services: REST, gRPC, Protocol Buffers or similar API technologies
- Data storage systems: PostgreSQL, Redis or similar databases
- Container technologies: Docker, Kubernetes or similar orchestration platforms
- Experience with CI/CD pipelines and testing in cloud environments (AWS/Azure/GCP)
- Strong debugging skills with ability to troubleshoot complex distributed systems
- Experience with cloud performance testing and monitoring tools (e.g., JMeter, Gatling, New Relic, Datadog, Prometheus/Grafana)
Desired Qualifications
- Experience testing AI/ML systems, LLM applications, or prompt engineering security
- Performance testing experience with large-scale SaaS products handling high throughput, concurrent users, and distributed architectures
- Familiarity with ML development lifecycle, model training, evaluation, and deployment
- Hands-on experience with AI efficacy testing, adversarial testing, or red teaming
- Experience with browser extension testing frameworks
- Background in API gateway testing (Kong, Envoy, LiteLLM, etc.)
- Experience with Model Context Protocol (MCP) or agentic AI systems
- Experience scaling test infrastructure to support hundreds of engineers
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