Hire(d) better.
Hire(d) better.
Hire(d) better.
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
As a Repairs Lead within the Data Center Infrastructure organization, you will define and manage the end-to-end hardware repair program across Anthropic's growing fleet of data centers. You will be accountable for repair turnaround time and the compute returned to service across every site, covering server, GPU/accelerator, network, and optics break-fix, RMA and reverse logistics with OEMs and ODMs, and the spares and repair inventory that keeps repair SLAs achievable. As a subject matter expert in hardware operations, you will develop scalable repair processes and quality targets, set the standards that site operations partners and repair vendors execute against, and turn failure trends into fixes which are driven upstream with engineering and equipment partners. If you are experienced in at-scale datacenter hardware operations, are passionate about HPC data centers, & enjoy working in complex, fast-paced environments, we welcome you to apply.
Define the global repair strategy including repair SLAs, prioritization rules, escalation paths, and reporting methods, and drive standardization across all sites.
Own repair turnaround time and repair backlog across the fleet evidenced by Anthropic-owned ticket and telemetry dashboards you help develop.
Author and improve procedures for triage, break-fix, return-to-service validation, and train site operations partners on how to execute them.
Manage RMA and reverse logistics programs with OEMs, ODMs, and depot repair vendors, including warranty claims, return cycle times, and failure analysis feedback.
Set spares pool sizing and stocking levels by site and part, in coordination with supply chain and asset management, so that parts availability never gates repair SLAs.
Analyze failure patterns across sites to identify root causes and drive corrective actions with hardware engineering, suppliers, and site operations owners.
Lead the operating cadence with vendor and site leads, including weekly repair reviews, scorecards, and business reviews, and drive corrective actions for SLA excursions.
Communicate repair constraints, risks, and fleet availability impact to engineering and leadership.
Have 8+ years of experience in data center operations as a manager, technical lead or related role, including accountability for production availability.
Can demonstrate a proven track record running break-fix programs at a large scale across multiple sites.
Have managed vendors, OEMs, or contract workforces to measurable outcomes: SLAs, operational reviews, and corrective action.
Possess hands-on technical depth in server, network, and rack-level hardware, enough to independently verify repair quality and audit vendor claims.
Have built or substantially improved operational processes.
Are comfortable working with ticket, telemetry, and inventory data to drive decisions.
Possess a bachelor's degree in relevant domain or equivalent practical experience.
Experience with GPU/accelerator or high-density liquid-cooled infrastructure, including tray, cold plate, and manifold-level repair.
Experience managing RMA and warranty programs with hyperscale OEMs/ODMs, including failure analysis and supplier quality engagement.
Experience with spares planning, reverse logistics, or depot repair at data center scale.
Experience delivering repair outcomes inside partner-operated or colocation sites where on-the-floor operations are staffed via third parties.
Familiarity with optics and high-speed interconnect failures.
The annual compensation range for this role is listed below.
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
Will AI replace this role?
Check AI displacement risk, transferable skills, and career alternatives for Repairs Program Lead - Data Center Operations
The salary range for the Repairs Program Lead - Data Center Operations position at Anthropic is USD 320k+/yr.
The Repairs Program Lead - Data Center Operations position at Anthropic is based in Remote-Friendly (Travel Required); San Francisco, CA; Remote-Friendly US (Travel Required). This is a remote position.
The Repairs Program Lead - Data Center Operations position at Anthropic is a Contract role.
The Repairs Program Lead - Data Center Operations position at Anthropic requires 8+ yrs exp.