Senior Software Engineer (Kernel Programming)

Sophos is a cybersecurity leader defending 600,000 organizations globally with an AI-driven platform and expert-led services. Sophos meets organizations wherever they are in their security maturity and grows with them to defeat cyberattacks. Its solutions combine machine learning, automation, and real-time threat intelligence with frontline human expertise from Sophos X-Ops to deliver advanced, 24/7 threat monitoring, detection, and response.

Sophos offers industry-leading managed detection and response (MDR) alongside a comprehensive portfolio of cybersecurity technologies — including endpoint, network, email, and cloud security, extended detection and response (XDR), identity threat detection and response (ITDR), and next-gen SIEM. Together with expert advisory services, these capabilities help organizations proactively reduce risk and respond faster, with the visibility and scalability needed to stay ahead of evolving threats.

Sophos goes to market with a global partner ecosystem, including Managed Service Providers (MSPs), Managed Security Service Providers (MSSPs), resellers and distributors, marketplace integrations, and cyber risk partners, giving organizations the flexibility to choose trusted relationships when securing their business. Sophos is headquartered in Oxford, U.K. More information is available at www.sophos.com.

Role Summary

We are looking for a Senior Software Engineer with strong hands-on expertise in C, Linux, kernel fundamentals, and CI/CD automation, along with solid experience in building systems and toolchains, to join our Linux Platform Engineering team. This role spans hardware platform bring-up, OS library and toolchain upgrades, cryptography and compliance initiatives, and deep system-level debugging across the hardware–kernel–software stack.

We value engineers who are open to adopting modern AI-assisted development workflows to enhance coding efficiency, debugging, automation, and documentation. Candidates who have partially or fully integrated AI tools into their day-to-day SDLC will have a distinct advantage.

The Linux Platform Engineering team builds and maintains the core system foundation across hardware and software layers, with strong expertise in C, Linux kernel fundamentals, build systems, and CI/CD automation. The team drives platform bring‑up, OS library and toolchain upgrades, security and compliance initiatives, and complex system‑level troubleshooting, while actively using AI‑driven SDLC practices to improve development efficiency, debugging, automation, and documentation quality.

Leverage AI-assisted workflows across the engineering lifecycle—analysis, development, test automation, debugging, documentation, and DevOps—to deliver faster, higher-quality outcomes

Enable and support Linux-based software platforms on new hardware architectures and SoCs

Upgrade, patch, and validate core OS libraries, toolchains, and platform dependencies

Contribute to cryptography, security, and compliance-driven platform initiatives

Perform deep system-level debugging across hardware, kernel, build, and user-space layers

Plan, integrate, and validate complex tool chain and dependency changes within CI/CD pipelines, ensuring stability and quality at scale

5-10 years of professional software engineering experience

Strong programming skills in C/C++

Solid understanding of Linux internals and kernel fundamentals

Strong working knowledge of build systems, with hands-on experience in CI/CD automation

Proficiency in writing, reading, and debugging Make files, including multi-target, recursive, and cross-compilation setups

Working proficiency in Python, Perl, or Bash for automation, integration, and debugging

Familiarity with Docker, YAML, JSON, SQL, and the broader open-source ecosystem

Experience with open-source packaging, dependency management, patching, and platform integration

Strong analytical and troubleshooting skills across hardware and software boundaries

Good to have skills:

Hands-on experience with AI-assisted engineering tools (e.g., AI coding assistants, AI-driven code review, debugging, test generation, or documentation), with partial or full adoption welcomed

Experience working in, or interest in shaping, an AI-driven SDLC environment

Good understanding of Go programming language

Exposure to agentic AI workflows for engineering productivity

Experience with OpenWrt, Bazel, or similar build ecosystems

Knowledge of networking and cryptography

Experience in compliance-oriented engineering environments (e.g., FIPS, Common Criteria)