Principal Cloud Architect

Responsibilities

• Design end-to-end platform patterns, build reference implementations, document architectural rationale, and partner with implementation teams on rollout.
• Participate in weekly architecture reviews using a consistent, documented rubric; expand standards libraries and Architecture Decision Records (ADRs).
• Provide architectural stewardship in cloud infrastructure and/or data architecture, including runtime platforms, networking, service mesh, containers, infrastructure scalability, resilience, security, event streaming, databases, pipelines, warehouses, and lakehouses.
• Evaluate emerging technologies through structured proofs of concept, establish technology onboarding and phase-out standards, and assess vendor changes and consolidation opportunities.
• Partner with FinOps on cost optimization, including AI and model infrastructure spending.
• Host design reviews and workshops, consult with engineering teams on complex infrastructure decisions, and create self-service architectural patterns.
• Contribute to multi-year platform strategy involving developer experience, delivery pipelines, and AI-augmented architecture review tooling.

Requirements

• Proven experience setting technical direction across large-scale systems used by multiple teams, including cloud, networking, data, or delivery platforms.
• Production experience with GCP and/or AWS and practical Kubernetes experience, such as GKE or an equivalent platform.
• Strong proficiency with Terraform, GitOps workflows, and reusable infrastructure modules.
• Depth in at least one of the following domains:
  • Cloud infrastructure: cloud-native networking, Kubernetes, service mesh, mTLS, scalability, resilience, cost efficiency, infrastructure security, AWS transit patterns, GCP Shared VPCs, Private Service Connect, and VPC peering.
  • Data architecture: Kafka/Confluent, Pub/Sub, PostgreSQL, Cloud SQL, MongoDB, Snowflake, BigQuery, Solr, Elasticsearch, Dataflow, Cloud Composer, MSK, Kinesis, and Apache Iceberg.
• Ability to write code, build working prototypes, and evaluate system behavior under load, including incidents, on-call impact, capacity, and rollout blast radius.
• Strong technical leadership, writing, presentation, and cross-organizational influence skills without formal managerial authority.
• Experience conducting technology evaluations, proofs of concept, and actionable architectural recommendations.
• Working knowledge of AI/ML infrastructure, including model serving, vector databases, and inference cost and latency trade-offs.
• Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.
• 10–15+ years of cloud infrastructure, platform, DevOps, or data architecture experience.

Nice-to-Haves

• Depth in both cloud infrastructure and data infrastructure.
• Experience with GCP organization-level policies, folder structures, and IAM inheritance design.
• Confluent Platform experience with Schema Registry, Kafka Connect, or ksqlDB.
• Experience with an Architecture Review Council or equivalent governance body.
• Experience building or applying AI-augmented architecture review workflows, including MCP servers or LLM-based rubric evaluation.
• MLOps experience with MLflow, Kubeflow, Vertex AI Pipelines, or SageMaker.

Compensation and Benefits

• Base salary range: $157,500–$247,500 USD.
• Additional compensation such as bonus, commission, equity, and benefits may apply.
• Benefits include comprehensive programs supporting employees' and families' mind, body, lifestyle, and overall well-being.