About the Job:
Red Hat is seeking a Senior Site Reliability Engineer (SRE) to develop, scale, and operate our OpenShift managed cloud services. OpenShift is Red Hats enterprise Kubernetes distribution. As an SRE you will contribute to running OpenShift at scale by enabling customer self-service, making our monitoring system more sustainable, and eliminating work through automation. This role requires a strong coding background, with approximately 70% development responsibilities and 30% dedicated to on-call duties.
On the SRE team, you will have the opportunity to influence the complex challenges of scale which are unique to Red Hat managed cloud services, while using your skills in coding, operations, and large-scale distributed system design.
In this role, you will work at the intersection of software engineering and operations, ensuring reliability, scalability, and performance of large-scale distributed systems. Youll leverage automation, coding, and observability practices to eliminate toil, build resilience, and continuously improve our services.
This is a unique opportunity to work on complex, high-scale challenges while collaborating in a global, transparent, and open culture where innovation, experimentation, and continuous learning are part of the DNA
What you will do?
The day-to-day responsibilities of an SRE involve working with live systems and coding automation. As an SRE you will be expected to:
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Contribute code to increase the scalability and reliability of the service
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Contribute software tests and participate in peer review to increase the quality of our codebase
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Help and develop peers capabilities through knowledge sharing, mentoring, and collaboration
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Participate in a regular on-call schedule, including occasional paid weekends and holidays
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Practice sustainable incident response and blameless postmortems
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Resolve customer issues escalated from the Red Hat Global Support team
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Work within a small agile team to develop and improve SRE software, support your peers, plan and self-improve
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Proactively utilize AI-assisted development tools (e.g., GitHub Copilot, Cursor, Claude Code) for code generation, auto-completion, and intelligent suggestions to accelerate development cycles and enhance code quality.
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Demonstrate proficiency in utilizing LLMs (e.g., Google Gemini), as relevant, for tasks such as brainstorming solutions, deep research, summarizing technical documentation, drafting communications, summarizing complex technical information, and enhancing problem-solving efficiency across the development lifecycle.
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Proactively utilize AI-assisted development tools (e.g., GitHub Copilot, Cursor, Claude Code) for code generation, auto-completion, and intelligent suggestions to accelerate development cycles and enhance code quality.
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Participate in AI-assisted code reviews, utilizing tools that provide real-time feedback, identify potential bugs, security vulnerabilities, and adherence to coding standards, contributing to a more thorough and efficient review process.
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Explore and experiment with emerging AI technologies relevant to software development, proactively identifying opportunities to incorporate new AI capabilities into existing workflows and tooling.
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Collaborate with cross-functional teams to identify opportunities for AI integration within the software development lifecycle, driving continuous improvement and innovation in engineering practices; share use cases for successful experiments with stakeholders for broader use.
What you will bring?
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Bachelors degree in Computer Science, Engineering, or related field; equivalent practical experience will also be considered.
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5+ years of experience in at least one programming language (Python, Golang, Java)
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Hands-on experience with public cloud platforms (AWS, GCP, Azure). Preferably Azure
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4+ years of experience with Kubernetes OR Openshift
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Experience with Docker based containers
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Strong collaboration and problem-solving skills in distributed, team-based environments.
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Experience troubleshooting as-a-service offerings (SaaS/PaaS) and working with complex distributed systems.
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Working knowledge of Linux/Unix operating systems.
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Proven ability to automate repetitive tasks and debug performance issues.
Following are considered a plus:
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5+ years of experience managing Linux servers running Red Hat Enterprise Linux (RHEL), CentOS, or Fedora hosted at a cloud provider such as Amazon Web Services (AWS), Google Compute Engine (GCE), or Microsoft Azure
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3+ years of experience with enterprise systems monitoring; knowledge of Prometheus is a plus
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3+ years of experience with enterprise configuration management software like Ansible by Red Hat, Puppet, or Chef
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2+ years of experience delivering a hosted service
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Demonstrated ability to quickly and accurately troubleshoot system issues
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Solid understanding of standard TCP/IP networking and common protocols like DNS and HTTP
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Solid communications skills and experience working directly with and presenting to customers
