AI-First Generalist Engineer (Patch Backporting Infrastructure)

The company is hiring remote specialists who have already relocated from Russia/Belarus.

Description

• 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 all are successful. We are truly a great place to work. Check out our website for more information.
• 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 of CentOS, Ubuntu, Debian, Oracle Linux, PHP, Python, Spring frameworks, Angular/AngularJS, Django, Flask. For more information, visit our website.

We're looking for AI-First Generalist Engineer. Patch Backporting Infrastructure to join our team tackling the challenge of AI-powered patch backporting.

The Mission

We automate patch management and vulnerability mitigation across large-scale Linux systems, powered by AI. We need a generalist engineer who doesn't just "use" AI tools occasionally — but who develops through AI agents as a default working mode. You'll orchestrate AI-assisted coding tools to design, build, test, and ship services, data pipelines, and automation infrastructure that our backporting platform runs on.

You'll own critical workstreams end-to-end: transitioning services onto a new Automation Pipeline, onboarding a new product, migrating historical data — all at a pace that's only possible when AI agents are first-class participants in your development workflow. The stack is primarily Python today, but we're hiring for engineering versatility, not language loyalty.

What You'll Drive

1. AI-First Engineering & Infrastructure

• Build and extend services, CLIs, and data pipelines — using AI agents as your primary development lever to achieve extreme iteration speed.
• Adjust and enhance the existing AI-powered backporting automation to handle new data types and product requirements.
• Migrate tens of thousands of entries of historical data between storage systems while maintaining compatibility with downstream tooling.
• Design and implement workflows for features currently missing from the automation pipelines.
• Treat iteration velocity as a first-class metric — build the way you ship: fast, measurable, and with AI doing the heavy lifting on boilerplate, tests, and scaffolding.

2. Platform Transition & Delivery

• Drive the migration of teams and services from the legacy pipeline to the new Automation Pipeline infrastructure, ensuring zero disruption to ongoing backporting work.
• Audit both old and new pipeline implementations — make sure nothing viable is lost in transit.
• Onboard the new product seamlessly into the existing ecosystem, designing any missing integrations along the way.

3. Collaboration & Scaling

• Collaborate across units to onboard more customers and domains onto the shared benchmarking infrastructure.
• Bypass the documentation tax: leverage AI to automate knowledge sharing, onboarding artifacts, and technical documentation — the team scales through high-signal artifacts, not meetings.
• Share updates on delivered features effectively and asynchronously.
• Requirements.

What You'll Bring

Must-Haves

• Bachelor's or Master's in Computer Science, Engineering, or a related field.
• 3+ years of professional experience as a developer or engineering lead.
• Generalist engineering DNA — comfortable across the stack: backend services, CI/CD pipelines, data migrations, infrastructure-as-code. You pick up whatever language or tool the problem demands.
• Hands-on LLM integration — experience calling LLM APIs (OpenAI, Anthropic, etc.) and familiarity with techniques like RAG, CAG, and agentic patterns.
• AI-native development workflow — you actively use AI coding agents (Cursor, Windsurf, aider, Claude Code, etc.) not as a novelty but as your primary mode of building software.
• Infrastructure skills — CI/CD (Jenkins / GitLab CI), containerization (Docker), testing automation.
• Experience establishing projects from scratch, including basic DevOps setup.
• Ownership mindset — you find bottlenecks and build the tooling to remove them, without waiting for a ticket.
• Cross-functional teamwork — proven ability to coordinate across multiple teams.
• Effective asynchronous and remote communication.

Nice-to-Haves

• Proficiency in Python — including advanced topics: multithreading, async, networking, OS internals (the current codebase is predominantly Python).
• Published research or experience validating engineering hypotheses through experiments.
• Data analysis skills — representing results, building metrics.

Why Join Us

• You'll work at the intersection of AI and critical software infrastructure — Linux security patching at massive scale. We're building a team where AI-first development is the norm, not an experiment. You'll be empowered to own your work end-to-end, ship fast, and push the boundary of what a single engineer can deliver when AI agents are part of the workflow.

Benefits

What's in it for you?

• A strong focus on professional development with opportunities for learning and growth:
  • Interesting and challenging projects
  • Mentor and other knowledge-exchange programs
• Fully remote work with flexible working hours, that allows you to schedule your day and work from any location worldwide.
• Paid 24 days of vacation per year, 10 days of national holidays, and unlimited sick leaves to ensure you maintain a healthy work-life balance.
• Compensation for private medical insurance.
• Co-working and gym/sports reimbursement.
• The opportunity to receive a reward for the most innovative idea that the company can patent, fostering a culture of creativity and innovation.