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Company Overview
A leading U.S.-based healthcare organization is seeking a Principal Architect to shape observability and hybrid cloud practices across its enterprise. The organization delivers innovative health solutions, connecting patients, providers, and systems through advanced technology, cloud infrastructure, and AI-driven analytics to improve healthcare experiences and operational efficiency.
Summary
The Principal Architect will own enterprise observability and hybrid cloud architecture, establishing standards, reference designs, and technical direction for monitoring and multi-cloud infrastructure. This hands-on role requires building pipelines, defining telemetry strategies, and guiding teams in best practices for observability and cloud operations.
Responsibilities
Observability
Own the enterprise observability reference architecture covering metrics, logs, traces, and events across all environments (cloud and on-prem)
Drive an OpenTelemetry-first instrumentation strategy, including standard libraries, semantic conventions, collector topologies, and pipeline design
Build and operate telemetry pipelines on Grafana Mimir, Loki, and Tempo, including multi-tenant configurations, retention policies, and capacity planning
Define reliability measures: SLOs, SLIs, error budgets, and alerting frameworks consistently across all lines of business
Integrate observability tooling with incident management platforms such as ServiceNow ITOM and xMatters
Establish telemetry schema standards to ensure teams emit actionable and technically compliant data
Hybrid Multi-Cloud
Build and maintain reference architectures for hybrid environments: OpenShift on-prem with KVM/libvirt and Dell PowerFlex storage, plus Azure, AWS, and GCP
Lead standards for workload identity and federation using SPIFFE/SPIRE and cloud-native IAM patterns
Provide guidance on compute runtime selection (containers, VMs, bare metal, serverless) with a clear decision framework
Connect autoscaling and capacity planning behavior to telemetry signals
Advance FinOps maturity by integrating cost data, establishing unit economics, and promoting open billing standards
AI + Observability
Identify opportunities for AI/ML in observability: anomaly detection, root cause analysis, log clustering, and smarter alerting
Define observability standards for AI-powered systems, covering latency, token costs, model drift, and related signals
Ensure new AI-powered platforms are instrumented correctly from day one
Required Qualifications
10+ years in infrastructure, cloud architecture, platform engineering, or SRE
8+ years of architecture experience in observability, cloud infrastructure, or both
Solid experience with at least two of Azure, AWS, or GCP, including networking, identity, compute, and storage
5+ years with Kubernetes in production (OpenShift, EKS, AKS, or GKE)
5+ years with OpenTelemetry or similar frameworks (collectors, SDKs, semantic conventions, pipeline design)
5+ years with observability platforms: Grafana/Mimir/Loki/Tempo, Prometheus, Datadog, Splunk, Dynatrace, or comparable tools
Experience defining SLOs/SLIs and building alerting strategies at an organizational level
Proven track record writing architecture standards that teams adopted
Strong communication skills with engineers and senior leadership
FinOps background: cloud cost optimization, chargeback, unit economics
Service mesh (Istio, Envoy, Linkerd) or eBPF-based tools (Cilium, Pixie)
Engagement in open-source communities (CNCF, OpenTelemetry)
Healthcare, insurance, or financial services experience (HIPAA/SOX familiarity)
Cloud certifications are a plus but not required
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