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Technical Lead; Quality Assurance

Job in San Jose, Santa Clara County, California, 95199, USA
Listing for: Spectro Cloud
Full Time position
Listed on 2026-10-17
Job specializations:
  • Software Development
    DevOps, Cloud Engineer - Software
Salary/Wage Range or Industry Benchmark: 180000 - 240000 USD Yearly USD 180000.00 240000.00 YEAR
Job Description & How to Apply Below
Position: Technical Lead (Quality Assurance)
  • 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, Dev Ops, and Product teams throughout the release lifecycle
  • From defining release test strategies in Test Rail 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, Open Telemetry) 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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