Principal Software Engineer, Endpoint Platform

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

• Build native endpoint agents for Windows, macOS, and Linux.

• Develop the integrated privileged access client within the endpoint agent.

• Implement Privileged Endpoint Device Management (PEDM) policy enforcement.

• Build secure communication between Endpoint Agents and Edge Backends with resilient fail-closed behavior.

• Develop local telemetry collection covering applications, processes, services, users, and endpoint posture.

• Detect Shadow IT, unauthorized applications, AI agents, automation agents, MCP servers, and developer tooling running on endpoints.

• Discover local resource access, including filesystem, browser data, credentials, local databases, network shares, and APIs.

• Optimize agent performance, scalability, reliability, and resource utilization.

• Lead architecture and mentor engineers building endpoint platform capabilities.

AI & Agentic Engineering

• Leverage AI-assisted software development throughout the SDLC.

• Build capabilities to discover, inventory, and govern AI agents and agentic workloads executing on enterprise endpoints.

• Develop secure endpoint capabilities supporting AI-native enterprise environments.

• Apply AI SDLC best practices across development, testing, deployment, and operations.

WHAT YOU BRING

• 1+ years of Principal-level of systems software engineering experience.

• Strong C++, Rust, or Go programming experience.

• Deep knowledge of Windows, macOS, or Linux internals.

• Experience with endpoint security products, including EDR, XDR, DLP, endpoint management, and PAM/PEDM.

• Experience with operating system security, process management, filesystem monitoring, ETW, eBPF, or similar platform technologies.

• Strong debugging, performance tuning, and systems engineering skills.

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

• Understanding of AI agents, LLMs, MCP, and modern AI application architectures.

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

• Strong leadership, design, and mentoring skills.