2 months ago
Milpitas, CA, USA or Vancouver, WA, USAStaff+
Base Salary
$240k - $250k/yr
Responsibilities
- Design and operate infrastructure for Cloud and Edge platform deployments.
- Build deployment automation for distributed Edge PoPs across headquarters, branch offices, regional hubs, and customer data centers.
- Design highly available, secure fail-closed deployment architectures and resilient policy synchronization.
- Build CI/CD pipelines, release automation, upgrade orchestration, and lifecycle management for Cloud, Edge, and Endpoint components.
- Develop observability platforms covering logging, metrics, tracing, health monitoring, and audit pipelines.
- Automate provisioning, certificate lifecycle management, secrets management, and secure configuration distribution.
- Drive platform scalability, operational excellence, reliability, disaster recovery, and security.
- Build infrastructure supporting AI-native applications, AI services, and distributed agentic workloads.
- Apply AI-assisted engineering and AI SDLC practices across infrastructure, deployment automation, and platform operations.
- Evaluate emerging AI infrastructure technologies to improve engineering productivity and operational efficiency.
Requirements
- At least 1 year of Principal-level experience in platform engineering, DevOps, or Site Reliability Engineering.
- Deep experience operating Kubernetes and cloud-native platforms at enterprise scale.
- Strong experience with Terraform, Helm, GitHub Actions, ArgoCD, Ansible, or similar automation technologies.
- Experience with distributed networking, service meshes, proxies, DNS, load balancing, and TLS.
- Strong Linux systems administration and infrastructure automation experience.
- Experience deploying highly available distributed enterprise software across multiple customer environments.
- Hands-on experience with AI-assisted development tools such as GitHub Copilot, Cursor, Claude Code, Windsurf, or ChatGPT.
- Understanding of AI application architectures, AI agents, MCP, and AI-enabled infrastructure.
- Familiarity with AI SDLC practices including AI-assisted development, automated testing, CI/CD automation, observability, and responsible use of AI-generated code.
- Strong operational mindset with communication, collaboration, and leadership skills.
Benefits
- Growth and learning opportunities through challenging, high-impact work.
- Welcoming and positive work environment at a high-growth Platform as a Service company.
- Equal opportunity workplace with annual security training and adherence to information security and privacy policies.
Tech Stack
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