Senior Customer AI Engineer

Nebius Group

. Lead customers’ transition from proof-of-concept to production .

Posted 10/12/2026full-timeRemote • United StatesSenior💰 $209,800 - $262,200 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in managing customer transitions to production environments, ensuring optimal performance and cost efficiency while effectively communicating complex technical concepts. Proficient in troubleshooting and optimizing AI/ML workloads and distributed systems.

Highest-signal resume keywords

Inference FrameworksCloud Infrastructure SystemsDistributed SystemsAI/ML WorkloadsSolutions Engineering

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Inference FrameworksCloud Infrastructure SystemsDistributed SystemsAI/ML WorkloadsTroubleshootingPerformance OptimizationGPU WorkloadsTechnical SupportSolutions EngineeringSRE

Soft Skills

Clear CommunicationOwnershipProactive MindsetSolution-OrientedTime Management

Industry Keywords

B2B EnvironmentsHigh-Load ApplicationsProduction IssuesCustomer WorkloadsTechnical Customers

Tech Stack

Tools & technologies

CloudDistributed Systems

About the role

Key responsibilities & impact

Lead customers’ transition from proof-of-concept to production
Ensure customer workloads are deployed, stable, scalable, performant, reliable, and cost-efficient
Drive time-to-production and time-to-value
Understand customer architectures and use cases
Monitor and improve latency, throughput, cost efficiency, and reliability
Identify and resolve bottlenecks proactively
Work directly with customer engineering teams
Provide guidance on best practices and optimisation
Translate technical challenges into actionable solutions
Act as the primary technical contact for production issues
Coordinate with internal teams to resolve incidents
Communicate clearly during high-pressure situations
Identify opportunities to optimise and expand usage
Provide structured feedback to Product and Infrastructure teams
Help shape better solutions based on real customer needs
Collaborate with Solution Architects and Product/Infrastructure teams to drive stable, performant, and cost-efficient deployments

Requirements

What you’ll need

Practical knowledge of inference frameworks such as vLLM, TensorRT, or similar
Solid understanding of cloud or infrastructure systems
Solid understanding of distributed systems or high-load applications
Understanding of AI/ML workloads, including LLMs and inference, is a strong plus
Ability to troubleshoot and reason about system performance
Experience working directly with technical customers, such as engineers and ML teams
Ability to communicate complex topics clearly and effectively
Strong sense of ownership and outcome-oriented execution
Ability to manage multiple customers and priorities
Structured, proactive, and solution-oriented mindset
Experience with GPU workloads or AI infrastructure is an added bonus
Background in solutions engineering, SRE, or technical support in B2B environments is an added bonus
Applicants must be authorized to work in the country in which they apply and provide proof of employment eligibility

Benefits

Comp & perks

100% company-paid medical, dental, and vision coverage for employees and families
401(k) plan with up to 4% company match and immediate vesting
20 weeks paid parental leave for primary caregivers
12 weeks paid parental leave for secondary caregivers
Remote work reimbursement up to $85/month for mobile and internet
Company-paid short-term disability, long-term disability, and life insurance coverage
Competitive compensation
Career growth and learning opportunities
Flexibility and ownership
Collaborative and innovative culture
Opportunity to work on impactful AI projects
International environment and talented teams