Senior Software Engineer, Windows - AI Security & Governance (Elara)

Omnissa•Atlanta, GA

2d•$141,000 - $250,000•Hybrid

About The Position

Omnissa is hiring a Senior Software Engineer to build Elara’s Windows agent, a lightweight, native, always-on component that helps enterprises discover, monitor, and govern AI use across devices. The agent provides visibility into AI applications in use, network destinations, and the handling of sensitive data. The role will help shape the product’s foundations and define how agent-assisted engineering is used to develop an enterprise security product. The engineer will make foundational architecture decisions, co-design shared components across platforms, and build reliable, resource-efficient Windows security components using Rust. AI coding agents are part of the development workflow, while engineers remain accountable for architecture, security decisions, and final review. Strong documentation, CI, and test automation are important guardrails for this work. The position is hybrid and located in Atlanta, Georgia, or Mountain View, California. No travel is expected. A bachelor’s degree is preferred, or an equivalent combination of education and relevant professional experience. The position is not eligible for employment-based immigration sponsorship.

Requirements

At least 5 years of software engineering experience, including significant experience developing native Windows applications, services, or system-level components.
Strong programming expertise in Rust.
Deep understanding of Windows internals, including processes, threads, memory management, IPC, file systems, and networking.
Experience with Windows APIs such as Win32, ETW, WFP, Windows Services, or Windows SDK.
Strong knowledge of TCP/IP, DNS, TLS, HTTP/HTTPS, VPNs, proxies, and network traffic inspection.
Experience developing multithreaded, asynchronous, event-driven, or long-running background applications.
Understanding of secure coding practices, memory safety, concurrency, authentication, and encryption.
Experience debugging, profiling, and troubleshooting native Windows applications.

Nice To Haves

Experience building endpoint security, EDR, DLP, VPN, ZTNA, SASE, or enterprise device-management products.
Hands-on experience with WFP callouts, ETW providers or consumers, Windows Filtering Platform APIs, or native security event monitoring.
Experience with Windows kernel-mode development, file-system minifilter drivers, or Windows Driver Frameworks (WDF).
Experience using on-device SLMs (Small Language Models).
Familiarity with Windows security architecture, access tokens, process privileges, service isolation, and protected processes.
Familiarity with Rust Tokio, Serde, windows/windows-sys crates, and native FFI integration.
Experience with gRPC, Protocol Buffers, and secure communication with cloud-based services.
Knowledge of Windows code signing, MSI/MSIX packaging, enterprise software deployment, and secure update mechanisms.
Familiarity with browser extensions, AI applications, or enterprise AI governance.

Responsibilities

Make foundational architecture decisions for the Elara Windows agent and co-design shared components across platforms.
Write specifications, design documents, and interface contracts that engineers and AI agents can use.
Build guardrails that support safe agent-assisted development.
Design, develop, and maintain native Windows endpoint security agents using Rust and Windows system APIs.
Integrate with ETW, WFP, Win32 APIs, and Windows Services for process monitoring, network visibility, and security enforcement.
Build reusable cross-platform security components and native Windows integrations for enterprise endpoint environments.
Optimize CPU utilization, memory footprint, event-processing throughput, and latency for continuously running Windows services.
Build resilient background services with crash recovery, secure installation and updates, and tamper-resistance mechanisms.
Troubleshoot complex Windows issues using WinDbg, ETW tracing, Windows Performance Analyzer, and other native debugging tools.
Use AI coding agents for implementation, test generation, refactoring, and debugging while retaining responsibility for architecture, security decisions, and final review.