Technical Lead

Who you are

• 12+ years of IT experience with a strong track record in software quality engineering and test automation for complex, distributed systems
• Bachelor's or Master's degree in Computer Science, Information Technology, or a related field, or equivalent practical experience
• 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 Kubernetes: architecture, operators, CRDs, scheduling, storage, and multi-cluster topologies (must-have)
• Subject-matter expertise in networking: TCP/IP, DNS, load balancing, CNI plugins, service mesh, ingress/egress, and network policies (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)
• Expert-level proficiency in Go, with production-quality code; comfortable reading and contributing to product code, not only test code
• Extensive hands-on experience with containers and cloud platforms (AWS, Azure, GCP, or VMware/bare-metal)
• 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
• Proven ability to influence engineering peers and leadership without direct authority
• Strong understanding of modern testing methodologies: contract testing, chaos/resilience testing, performance and scale testing, and CI/CD-driven quality gates
• 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

What the job involves

• 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