Principal Software Engineer, Platform Engineering & Edge Infrastructure
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
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Design and operate the infrastructure powering Cloud and Edge platform deployments.
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Build deployment automation for distributed Edge PoPs supporting headquarters, branch offices, regional hubs, and customer data centers.
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Design highly available deployment architectures supporting secure fail-closed operation and resilient policy synchronization.
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Build CI/CD pipelines, release automation, upgrade orchestration, and lifecycle management for Cloud, Edge, and Endpoint components.
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Develop observability platforms, including logging, metrics, tracing, health monitoring, and audit pipelines.
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Automate provisioning, certificate lifecycle management, secrets management, and secure configuration distribution.
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Drive platform scalability, operational excellence, reliability, disaster recovery, and security.
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Apply AI-assisted engineering across infrastructure, deployment automation, and platform operations.
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Build infrastructure supporting AI-native applications, AI services, and distributed agentic workloads.
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Follow AI SDLC best practices for software delivery, automation, deployment, monitoring, and continuous improvement.
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Evaluate emerging AI infrastructure technologies to improve engineering productivity and operational efficiency.
AI & Agentic Engineering
WHAT YOU BRING
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1+ years of Principal-level of platform engineering, DevOps, or Site Reliability Engineering experience.
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Deep experience operating Kubernetes and cloud-native platforms at enterprise scale.
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Strong experience with Terraform, Helm, GitHub Actions, ArgoCD, Ansible, or similar automation technologies.
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Experience with distributed networking, service meshes, proxies, DNS, load balancing, and TLS.
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Strong experience in Linux systems administration and infrastructure automation.
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Experience deploying highly available distributed enterprise software across multiple customer environments.
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Hands-on experience using AI-assisted development tools such as GitHub Copilot, Cursor, Claude Code, Windsurf, ChatGPT, or similar.
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Understanding of AI application architectures, AI agents, MCP, and AI-enabled infrastructure.
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Familiarity with AI SDLC best practices, including AI-assisted development, automated testing, CI/CD automation, observability, and responsible use of AI-generated code.
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Strong operational mindset with excellent communication, collaboration, and leadership skills.