Senior DevOps Engineer / Platform Engineer

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Job Title: Senior DevOps Engineer / Platform Engineer

Job Location: Santa Clara, CA

Job Type: Long Term Contract

Summary

Seeking a Senior DevOps Engineer to design, build, and scale infrastructure for a sitebuilder/network automation platform. This role focuses on CI/CD pipelines, Kubernetes deployments, managed databases, observability, Infrastructure as Code, secrets management, and environment reproducibility across dev, test, staging, and production. The engineer will transition the platform from manual operations to a productionready DevOps model.

Key Responsibilities

• CI/CD & Deployment: Build and maintain pipelines, ArgoCD workflows, and Helmbased Kubernetes deployments.
• Kubernetes & Runtime: Ensure reliability, resiliency, and troubleshooting for distributed services; define runtime requirements.
• Infrastructure as Code: Implement declarative IaC (Terraform) for AWS services including RDS/PostgreSQL, MongoDB, Redis.
• Data Services: Manage databases, snapshots, and restore workflows to support reproducible dev/test environments.
• Workflow Orchestration: Deploy and support Temporal for workflow automation.
• Observability: Implement monitoring/logging with Prometheus, Grafana, and tracing tools; define alerting and debugging practices.
• Security & Secrets: Manage secrets rotation, credential access, and secure integrations.
• Integrations: Support Nautobot and other service integrations with safe clientside patterns.
• Operating Model: Define DevOps/Development collaboration, incident readiness, and environment ownership boundaries.
  
  

Qualifications

• 7 years in DevOps/Platform/SRE roles.
• Strong Kubernetes, Helm, ArgoCD/GitOps, CI/CD experience.
• AWS managed services (RDS, DocumentDB, Redis), IaC (Terraform).
• Observability tools (Prometheus, Grafana).
• Scripting/automation (Python, Bash, Go).
• Strong Linux, networking, and distributed systems troubleshooting.
• Preferred: Temporal operations, MongoDB workflows, Nautobot/NetBox integration, multiregion scaling patterns.
  
  

Success Indicators

• Reliable CI/CD pipelines and standardized Kubernetes deployments.
• Infrastructure defined as code, reproducible environments.
• Stable Temporal, databases, cache layers, and observability tooling.
• Mature secrets/access management and clear DevOps operating model.