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Metro role with mid-level experience but niche Kubernetes/observability/Go requirements and moderate brand recognition.
Platform and Kubernetes expertise is transferable across industries but still favors operations-focused backgrounds.
Explicit 5+ years plus mandatory Go, Kubernetes, observability and cloud-native requirements create strict filters.
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Design, build, operate, and own reliability for Go-based Kubernetes services forming the backbone of AI-assisted software delivery platform infrastructure.
Implement observability features (structured logging, distributed tracing, metrics) and define SLOs, runbooks; ensure production readiness and incident accountability.
Collaborate closely with ML and agentic systems engineers to provide reliable platform foundations and contribute to architecture decisions and AI tooling integration.
5+ years professional software engineering experience with senior-level impact.
Strong proficiency in Go with idiomatic, well-tested, production-quality code; experience with Kubernetes operations including debugging production incidents and understanding CRDs.
Hands-on experience with observability tools such as OpenTelemetry, Prometheus, and distributed tracing.
Cloud-native experience on AWS or GCP including IAM, managed Kubernetes, infrastructure-as-code; ability to work effectively in AI-augmented development workflows.
Experienced platform engineer skilled in operating end-to-end production systems with strong ownership of reliability and observability.
Comfortable leading platform initiatives integrating AI tooling into developer workflows and influencing build vs buy decisions.
Able to collaborate cross-functionally with ML and infrastructure teams, serving as a go-to expert for Kubernetes and observability challenges in AI-native environments.