Site Reliability Engineer - xAI Technical Operations

About xAI

xAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All engineers are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates.

About the Role

AI is building at a furious pace with the latest hardware to help people understand the universe and we are in need of Site Reliability Engineers (SREs) who have at least 5+ years of experience in distributed, internet-scale environments, including on-prem and cloud-based infrastructure.

You will own the availability and reliability of xAI's infrastructure and core services, including detecting issues, problem management, incident management, and root cause analyses (RCAs). Engineers will own the availability of xAI infrastructure and its operations processes applying concepts like failure domains, blast radii, and canary testing. You will be expected to participate in a team on-call rotation and to contribute to ushering xAI into the next generation of infrastructure management across multiple data centers and cloud environments.

Responsibilities Will Include

• Setting technical strategy and roadmap for infrastructure availability.
• Automating monitoring, alerting, and troubleshooting for high-availability services, while working with legacy systems to scale, improve, or deprecate.
• Owning incident response, problem management, and conducting thorough RCAs to prevent recurrence and drive continuous improvement.
• Analyzing performance metrics and service health to identify, resolve, and mitigate bottlenecks or failures in distributed environments.
• Ensuring security, scalability, and resilience of production infrastructure supporting AI workloads.

Location

Work will be in-office based out of either Palo Alto, California or Dublin, Ireland.

Travel to our Memphis office is both an expectation and requirement for this role.

Required Qualifications

• A minimum of 5 years of software, systems or reliability engineering experience.
• Experience managing services in distributed, internet-scale *nix environments, including on-prem and cloud (e.g., AWS, GCP).
• Development experience in Python, Scala, Java, C, or C++.
• Demonstrable knowledge of TCP/IP, HTTP, Networking and systems programming (e.g., bash and shell tools).
• Familiarity with containerization and orchestration tools (e.g., Kubernetes, Docker, Mesos) and systems management (e.g., Puppet, Chef, Ansible).
• Bachelor's degree in Computer Science, Electrical Engineering, or a related field (or equivalent experience).

Preferred Experiences

• Experience in on-call rotations and incident response in high-stakes environments.
• Experience with AI/ML infrastructure, large-scale GPU clusters
• Strong problem-solving skills and ability to thrive in a fast-paced, ambiguous setting.
• Comfortable with deployment, support, monitoring, administration, and troubleshooting across on-prem, cloud and hybrid infrastructures.
• Proven understanding of systems and application design, including operational trade-offs.

Interview Process

After submitting your application, the team reviews your CV and statement of exceptional work. If your application passes this stage, you will be invited to an initial interview (45 minutes - 1 hour) during which a member of our team will ask some basic questions. If you clear the initial phone interview, you will enter the main process, which consists of four interviews:

1. Coding assessment in a language of your choice.

2. Site reliability and operations technologies.

3. Manager Interview.

4. Meet and greet with the team with a presentation of a large scale solution or problem you owned, start to finish.

Our goal is to finish the main process within one week. We don’t rely on recruiters for assessments. Every application is reviewed by a member of our technical team. All interviews will be conducted via Google Meet.

Benefits

Base salary is just one part of our total rewards package at xAI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks.

xAI is an equal opportunity employer.

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