Cloud Linux Inc.

Full-Stack Lead Engineer for Code Reviewer Project

Remote Valencia, Spain
C++ JavaScript R Machine Learning Python Java
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 https://cloudlinux.com/

We are seeking a Senior Software Engineer to lead the development of a robust, multi-language code reviewer. The ideal candidate should excel in agile workflows, code review best practices, and software engineering life cycles. You will work with stakeholders to refine requirements and deliver an adaptable review tool that integrates seamlessly with various CI/CD pipelines (GitLab, GitHub, Gerrit, Jenkins) and supports deep code analysis—potentially leveraging AI/LLM techniques where beneficial.

Key Responsibilities

  • Code Reviewer Development
    • Design and implement a system capable of reviewing code across multiple languages and projects.
    • Incorporate advanced code analysis techniques (e.g., AST parsing, control flow analysis) to identify bugs, style inconsistencies, and potential security and performance issues.
    • Ensure the reviewer can be extended or customized based on evolving requirements from diverse teams.
  • Agile & DevOps Integration
    • Employ agile methodologies (Scrum/Kanban) to plan, track, and iterate on new features.
    • Integrate seamlessly with CI/CD pipelines (GitHub, GitLab, Gerrit, Jenkins), making the reviewer easily adoptable by various R&D teams.
    • Collaborate with DevOps to ensure smooth deployment and maintenance.
  • Expert Code Review Practices
    • Define and maintain code review standards, including style guidelines, security checks, and performance considerations.
    • Work with development teams to refine pull/merge request processes, fostering a culture of high-quality code.
    • Provide comprehensive review feedback and assist in automating repetitive checks to streamline manual review efforts.
  • Cross-Team Collaboration
    • Engage with stakeholders and engineering teams to gather feedback and requirements.
    • Communicate progress clearly and adapt the solution based on iterative input.
    • Advocate for best practices, teaching others how to maximize the value of automated reviews.
  • Research & Prototyping
    • Investigate emerging tools and methodologies in static analysis, linting, and machine learning for potential integration.
    • Prototype new features or approaches including AI/LLM usage to for code reviewing and unstructured data handling.
  • Software Engineering Lifecycle Expertise
    • Proven ability to take a project from concept through to production, including requirements gathering, design, testing, and maintenance.
  • Agile Methodologies & Tools
    • Experience with Jira (or similar) for task management, sprint planning, and reporting.
    • Comfortable with iterative development, frequent releases, and fast feedback cycles.
  • Version Control & CI/CD
    • Proficiency in Git-based workflows (GitHub, GitLab, or Gerrit) and CI/CD setups (Jenkins, etc.).
    • Strong knowledge of how to integrate automated checks and tests into pipelines.
  • Advanced Code Review
    • In-depth understanding of what makes a code review effective, including detection of security vulnerabilities, logical errors, performance bottlenecks, and style issues.
    • Familiarity with AST-based or control-flow techniques to enable deeper analysis.
  • Multi-Language Proficiency
    • Competency in at least one major language (e.g., Python, Java, C++, JavaScript), with an awareness of common design patterns, best practices, and typical pitfalls across various tech stacks.
  • Research & Prototyping Skills
    • Ability to independently explore new libraries or methods—especially around static analysis and potential AI-based enhancements—to continually improve the reviewer.

Nice-to-Have

  • LLM/AI Exposure
    • Experience applying Large Language Models or other AI/ML techniques to code analysis.
  • Customization Experience
    • Prior work extending or tailoring static analysis tools to match domain-specific requirements.
  • Performance & Security Audits
    • Background in detecting performance regressions or security vulnerabilities through automated scanning and analysis.
  • Startup or Fast-Paced Environment
    • Comfortable with rapid change, limited requirements, and tight delivery timelines.

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