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Milpitas, California, United States
Onsite
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.
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.
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.
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.