Senior AI Engineer - AI Patch Backporting (remote-only, Europe & CIS)

CloudLinux is a global remote-first company. We are driven by our principles: do the right thing, employees first, we are remote first, and we deliver high-volume, low-cost Linux infrastructure and security products that help companies to increase the efficiency of their operations. Every person on our team supports each other and does what we can to ensure we are all successful. We are truly a great place to work.

Check out our website for more information - https://cloudlinux.com/

Endless Lifecycle Support (ELS) enables organizations to continue securely using Linux distributions and software languages that have reached the end of life or no longer receive standard security support – delivering vulnerability patches for unsupported versions of CentOS, Ubuntu, Debian, Oracle Linux, PHP, Python, Spring frameworks, Angular/AngularJS, Django, Flask. For more information, visit our website: tuxcare.com/endless-lifecycle-support

We are looking for a Senior AI Engineer to join our ELS Backporting Research team.

The team is responsible for designing and building AI-driven tools that automate patch backporting and make it faster to deliver secure updates across multiple Linux distributions.

As a Senior Engineer, you will:

• Own key components such as the Patch Backporter library and benchmarking infrastructure.
• Design cross-component solutions to previously unsolved problems in automated patching.
• Integrate your solutions into our existing CI/CD and automation stack so they are used in production, not just in experiments.

You will work closely with the team lead on priorities and problem framing, but are expected to be independent in technical design and implementation details.

Responsibilities:

• Lead development of the Patch Backporter library:
• Design and evolve its architecture and abstractions.
• Keep it clean, composable, and extendable for new models and techniques.
• Design and lead major changes in patch backporting automation:
• Identify bottlenecks and weak points in current workflows.
• Propose and drive cross-component improvements end-to-end.
• Own and evolve benchmarking and evaluation infrastructure:
• Design metrics, datasets, and evaluation flows to measure backporter performance.
• Automate benchmarks in CI and make results stable and comparable over time.
• Integrate improvements into the existing automation stack:
• Plan and implement how backporter updates propagate into the broader automation ecosystem.
• Work with CI/CD, services, and databases so changes are fully wired into production.
• Accelerate iteration within the team:
• Build Python tools, CLIs, small services, and helpers that make experiments faster and cheaper.
• Improve local dev setups, test harnesses, and engineering processes for research.
• Collaborate and communicate:
• Work cross-functionally with other engineering teams to align on interfaces and integration points.
• Write clear technical documentation, design docs, and experiment logs.
• Mentor junior engineers and share knowledge on AI, infra, and tooling.