Support Engineering Team Lead

Details

Nebius is building a full-stack AI cloud platform for data and model training through production deployment. The role is a hands-on L3 Support Engineering Lead position responsible for resolving complex customer issues, providing technical direction, organizing team work, and supporting investigations across the Nebius platform. This is a remote position in North America.

Responsibilities

• Lead and support a small, distributed team of L3 Support Engineers.
• Plan, prioritize, and distribute work based on customer impact, technical complexity, and team capacity.
• Provide technical guidance and hands-on support for complex or high-impact customer issues.
• Coach engineers, share knowledge, and help the team become increasingly independent.
• Collaborate with L2 Support, pre-sales, post-sales, customer engineering, product, and engineering teams.
• Ensure escalations include the necessary technical context, evidence, and customer information.
• Determine whether issues belong to the platform, a customer environment, or another technical area, and involve appropriate specialists.
• Maintain high standards for troubleshooting, documentation, handoffs, and customer communication.
• Identify recurring issues and gaps in tooling, documentation, processes, or team knowledge, and drive practical improvements.
• Support team planning, coverage, and forecasting as the organization grows.
• Participate in scheduled operational or duty work when specialist expertise is required, which may occasionally include work outside standard business hours.
• Contribute to hiring and onboarding additional engineers.

Requirements

• Strong hands-on experience troubleshooting complex production, cloud, or infrastructure-related issues.
• Experience leading technical work, mentoring engineers, or coordinating a small team or task force.
• Clear and confident communication with customers, engineers, and cross-functional stakeholders.
• Strong working knowledge of Linux environments.
• Experience with Kubernetes and container-based platforms.
• Practical understanding of infrastructure fundamentals, including networking and storage.
• Familiarity with block, file, and object storage, with the ability to investigate issues across these technologies.
• Sound judgment when handling ambiguous or high-impact technical problems.
• Ability to organize work, set priorities, and keep multiple stakeholders aligned.
• Broad familiarity across AI and ML operations, GPU or high-performance computing workload scheduling, Kubernetes, cloud infrastructure, networking, and storage, with deeper expertise in at least one area.
• Fluent written and spoken English.

Preferred Qualifications

• Experience supporting GPU cloud infrastructure or AI/ML workloads.
• Experience planning or troubleshooting model deployments.
• Familiarity with Python or Bash scripting and technical automation.
• Experience in technical support, SRE, production operations, or customer engineering organizations.
• Experience collaborating with globally distributed teams providing 24/7 customer coverage.
• Familiarity with Slurm and workload scheduling in GPU or high-performance computing environments.

Benefits

• Base compensation range of $179,500–$224,300 USD.
• 100% company-paid medical, dental, and vision coverage for employees and families.
• 401(k) plan with up to a 4% company match and immediate vesting.
• Paid parental leave: 20 weeks for primary caregivers and 12 weeks for secondary caregivers.
• Remote work reimbursement of up to $85 per month for mobile and internet.
• Company-paid short-term, long-term, and life insurance coverage.
• Career growth and learning opportunities, flexibility and ownership, and the opportunity to work on impactful AI projects.
• Applicants must be authorized to work in the country in which they apply and provide proof of employment eligibility.