Technical Lead (Quality Assurance)

Spectro Cloud; San Jose (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Spectro Cloud is seeking a senior QA leader to own release quality for core platforms. You will design automated pipelines, regression suites, and AI-assisted workflows to accelerate test design, execution, and coverage.

Ideal candidates excel in Kubernetes, AI inference workloads, and building test automation frameworks across API and UI layers. Collaboration with software engineering and product teams is essential to deliver enterprise-grade releases.

Qualifications

• Must-have: subject-matter expertise in Kubernetes architecture, operators, CRDs, scheduling, storage, multi-cluster topologies
• Must-have: hands-on testing AI inference workloads with GPU-based serving and model deployment frameworks
• Must-have: strong testing methodologies including contract testing, chaos/resilience, performance/scale
• Must-have: production-quality Go code and ability to read/modify product code

Responsibilities

• Design and maintain automated release pipelines and regression tests across APIs, UIs, and backend services
• Lead test architecture and technical direction across multiple teams
• Define release test strategies, automate CI/CD release gates, validate upgrades and bug fixes

Skills

Go

Linux

Test automation

CI/CD

Release testing

Leadership

Cloud platforms

Kubernetes

LLM/GenAI inference

Networking

Education

Bachelor’s or Master’s in CS/IT or equivalent practical experience

Tools

Triton

vLLM

KServe

Godog

Prometheus

Grafana

Job description

• 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 experience12+ 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