Principal Software Engineer, Platform Engineering & Edge Infrastructure

Team: Software Engineering

Location: Milpitas, California, Vancouver

Commitment: Full-Time

Workplace Type: hybrid

Salary:

Come join us as founding members of Saviynt’s AI Security team and help us build out AI security for the world's leading enterprises.

WHAT YOU WILL BE DOING

• Design and operate the infrastructure powering Cloud and Edge platform deployments.

• Build deployment automation for distributed Edge PoPs supporting headquarters, branch offices, regional hubs, and customer data centers.

• Design highly available deployment architectures supporting secure fail-closed operation and resilient policy synchronization.

• Build CI/CD pipelines, release automation, upgrade orchestration, and lifecycle management for Cloud, Edge, and Endpoint components.

• Develop observability platforms, including 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.

AI & Agentic Engineering

• Apply AI-assisted engineering across infrastructure, deployment automation, and platform operations.

• Build infrastructure supporting AI-native applications, AI services, and distributed agentic workloads.

• Follow AI SDLC best practices for software delivery, automation, deployment, monitoring, and continuous improvement.

• Evaluate emerging AI infrastructure technologies to improve engineering productivity and operational efficiency.

WHAT YOU BRING

• 1+ years of Principal-level of platform engineering, DevOps, or Site Reliability Engineering experience.

• 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 experience in Linux systems administration and infrastructure automation.

• Experience deploying highly available distributed enterprise software across multiple customer environments.

• Hands-on experience using AI-assisted development tools such as GitHub Copilot, Cursor, Claude Code, Windsurf, ChatGPT, or similar.

• Understanding of AI application architectures, AI agents, MCP, and AI-enabled infrastructure.

• Familiarity with AI SDLC best practices, including AI-assisted development, automated testing, CI/CD automation, observability, and responsible use of AI-generated code.

• Strong operational mindset with excellent communication, collaboration, and leadership skills.