Senior Software Engineer, macOS - 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 the Elara macOS agent, a lightweight, native, always-on component of a product 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 offers early ownership in a small team building a new enterprise security product. The engineer will shape foundational architecture for the macOS agent and co-design components shared across platforms. The team uses AI coding agents such as Claude Code, Cursor, and GitHub Copilot throughout design, implementation, testing, and debugging. Engineers remain accountable for architecture, security decisions, and final review, and help establish safe, agent-assisted development practices through clear specifications, documentation, CI, test automation, reusable skills, and review standards. The position is based in Atlanta, Georgia, or Mountain View, California, with a hybrid work arrangement and no expected travel. A bachelor's degree is preferred, or equivalent education and relevant professional experience. The typical base salary range is USD $141,000–$250,000 per year; the role may also be eligible for a corporate bonus program. Compensation may vary based on location, experience, education, skills, and other factors. Omnissa offers benefits including employee ownership, health insurance, 401(k) matching, disability insurance, paid time off, and growth opportunities. This position is not eligible for employment-based immigration sponsorship.

Requirements

At least 5 years of software engineering experience, or equivalent depth, including significant hands-on work on native macOS applications or system-level components.
Strong Rust skills and working proficiency in Swift.
Deep understanding of macOS internals, including processes, threads, memory management, IPC, file systems, and networking.
Hands-on experience with at least one of Endpoint Security, Network Extension, System Extensions, or XPC.
Solid networking knowledge, including TCP/IP, DNS, TLS, HTTP/HTTPS, VPNs, and proxies.
Experience building secure, concurrent, long-running background services, with a strong grasp of memory safety and secure coding.
Hands-on experience using AI coding agents on real production work, with sound judgment about when to trust, verify, or reject their output.
Comfort with ambiguity and end-to-end ownership in a zero-to-one environment.

Nice To Haves

Experience building endpoint security, EDR, DLP, VPN, ZTNA, SASE, or device-management products.
Hands-on experience with NEFilterDataProvider, NEPacketTunnelProvider, NEDNSProxyProvider, or Endpoint Security authorization events.
Knowledge of macOS security architecture, including sandboxing, entitlements, TCC, and system-extension lifecycle management.
Experience with Apple code signing, notarization, and MDM-based deployment.
Familiarity with the Rust ecosystem for native work, including Swift/Objective-C FFI, Tokio, Serde, and cross-platform libraries.
Experience with gRPC, Protocol Buffers, and secure cloud-to-endpoint communication.
Experience with on-device model inference, such as small language models via Core ML, for classification or detection.
Familiarity with AI security risks such as shadow AI, data leakage through AI apps, and the security of agent tooling like MCP.
Experience shaping engineering practices, such as spec-driven development, test harnesses for AI-assisted workflows, or building agent tooling.
Open-source contributions or public technical work.
Bachelor's degree, or equivalent combination of education and relevant professional experience.

Responsibilities

Make foundational architecture decisions for the Elara macOS agent and co-design shared components across platforms.
Write specifications, design documents, and interface contracts that engineers and AI agents can use to execute work.
Build guardrails that make agent-assisted development safe.
Build native endpoint security capabilities using Apple system frameworks.
Implement monitoring of process, file-system, and application activity, with event-driven policy enforcement.
Build network visibility and filtering capabilities.
Help enterprises discover and govern AI usage on Macs in real time.
Troubleshoot complex issues using Instruments, LLDB, unified logging, and native profiling tools.
Use AI coding agents across design, implementation, testing, and debugging.
Critically review AI-generated code, particularly low-level and privileged code paths.
Help define and evolve agentic development practices, including context and prompting patterns and review standards.