S
Spectro Cloud
Technical Lead (Quality Assurance)
Skills
Google Cloud PlatformTesting & QAGrafanaAIAWSPrometheusLinuxKubernetesAzure
12 days ago
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Important information
Contract type:
Permanent
Salary:
$280,000 – $304,000 / year
Location:
San Jose, CA, USA
Work mode:
Onsite
Published on:
15 October 2026
What they need
- The Release Engineering QA team at Spectro Cloud owns the release quality of our core platforms
- We are the final gate before every GA, patch, and hotfix reaches enterprise customers
- We operate at the intersection of modern cloud-native technologies and release engineering discipline
- The team designs and maintains automated release pipelines and regression, upgrade, and compatibility test suites across APIs, UIs, and backend services, while pioneering AI-assisted workflows to accelerate test design, execution, and coverage
- Given the breadth of our enterprise offerings, we certify complex release matrices across diverse Kubernetes distributions (such as K8s, K3s, and RKE2), operating systems, cloud providers, edge topologies, and air-gapped environments
- As release quality advocates, we collaborate closely with Software Engineering, DevOps, and Product teams throughout the release lifecycle
- From defining release test strategies in TestRail and establishing automated CI/CD release gates to validating upgrades and verifying bug fixes, our mission is to deliver dependable, enterprise-grade releases to our global customers on a predictable cadence- Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field, or equivalent practical experience
- 12+ years of IT experience with a strong track record in software quality engineering and test automation for complex, distributed systems
- Subject-matter expertise in Kubernetes: architecture, operators, CRDs, scheduling, storage, and multi-cluster topologies (must-have)
- Hands-on experience testing AI inference workloads: GPU-based serving, model deployment frameworks (e.g., Triton, vLLM, KServe), throughput/latency benchmarking, and inference accuracy validation (must-have)
- Strong understanding of modern testing methodologies: contract testing, chaos/resilience testing, performance and scale testing, and CI/CD-driven quality gates
- Expert-level proficiency in Go, with production-quality code; comfortable reading and contributing to product code, not only test code
- Strong proficiency in Linux-based operating systems and low-level troubleshooting/debugging (must-have)
- Demonstrated experience leading test architecture and technical direction across multiple teams as a Staff or Principal-level individual contributor
- Extensive hands-on experience with containers and cloud platforms (AWS, Azure, GCP, or VMware/bare-metal)
- Proven ability to influence engineering peers and leadership without direct authority
- Deep, hands-on experience designing and building test automation frameworks from the ground up for both API and UI (must-have)
- Subject-matter expertise in networking: TCP/IP, DNS, load balancing, CNI plugins, service mesh, ingress/egress, and network policies (must-have)
- Deep experience leading development of automation using Go-based test frameworks like Godog at scale
- Experience testing Kubernetes lifecycle management, cluster APIs (CAPI), or edge/IoT Kubernetes deployments
- Experience with LLM/GenAI inference stacks, distributed inference, and GPU cluster operations
- CKA, CKAD, or CKS certification
- Experience with observability stacks (Prometheus, Grafana, OpenTelemetry) applied to test infrastructure
- Prior contributions to open-source Kubernetes or cloud-native testing projects
- Track record of setting and delivering on multi-quarter technical strategy for quality/automation organizations
- Experience partnering with customer-facing teams on escalations and driving preventative quality improvements from field learnings
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