Role description

Technical Lead (Quality Assurance)

Spectro Cloud

AI-native

TypeFull-time

WorkplaceOn-site

SeniorityStaff / Lead

Salary$280,000–$304,000

LocationSan Jose, CA

Posted10/15/2026

Engineering

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

Relevant archetypes

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Company info

Spectro Cloud

The fast lane to production AI.

Getting AI from pilot to production is a widespread problem. Spectro Cloud is the fast lane: we help enterprises, sovereign AI clouds and public sector organizations build, govern and operate AI infrastructure in any environment, from edge to cloud, and from metal to token factory. We're proud that customers like GE HealthCare, Yum! Brands, the U.S. Air Force, and other organizations trust us with their biggest infrastructure challenges, from zero-downtime operations across thousands of sites to standing up production AI in 30 days. Behind those results is PaletteAI, our AI infrastructure management platform built for scale. It's the only platform that manages VMs, containers and AI workloads in one place, with one operating model, and consistent policy, access and cost controls everywhere. It runs wherever you do, including air-gapped, sovereign and regulated environments. Every team starts somewhere, whether that's standing up an AI factory, cutting inferencing costs, moving off

Private company Series D Mega round

Role description

Technical Lead (Quality Assurance)

Relevant archetypes

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