Senior Customer AI Engineer - Token Factory

About the role

Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D.

We're looking for a Senior Customer AI Engineer who will join our Token Factory team to help our customers successfully transition from proof-of-concept to production and scale their AI workloads on Nebius infrastructure. This role sits at the intersection of engineering, delivery, and customer success – ensuring that what was promised during pre-sales actually works reliably in production. You will work closely with customer engineering teams, Solution Architects, and Product/Infrastructure teams to drive stable, performant, and cost-efficient deployments. This Role Is NOT A sales role (though you will support expansion through value) A pure support role (you won’t just react to tickets) A solution architect role (you won’t design systems from scratch) You’re welcome to work remotely from the United States.

Responsibilities

• Own the production journey
• Lead the transition from PoC to production
• Ensure customer workloads are deployed, stable, and scalable
• Drive time-to-production and time-to-value
• Ensure technical success in production
• Understand customer architectures and use cases
• Monitor and improve: performance (latency, throughput) cost efficiency reliability
• Identify and resolve bottlenecks proactively
• Act as a trusted technical partner
• Work directly with customer engineering teams
• Provide guidance on best practices and optimisation
• Translate technical challenges into actionable solutions
• Manage risks and incidents
• Act as a primary technical contact for production issues
• Coordinate with internal teams to resolve incidents
• Communicate clearly during high-pressure situations
• Drive continuous improvement
• Identify opportunities to optimise and expand usage
• Provide structured feedback to Product and Infrastructure teams
• Help shape better solutions based on real customer needs

Requirements

• Technical background: Practical knowledge of inference frameworks (e.g. vLLM, TensorRT, or similar); Solid understanding of: cloud or infrastructure systems, distributed systems or high-load applications; AI/ML workloads (LLMs, inference, etc.) is a strong plus; Ability to troubleshoot and reason about system performance.
• Customer-facing Experience: Experience working directly with technical customers (e.g. engineers, ML teams); Ability to communicate complex topics clearly and effectively.
• Ownership & execution: Strong sense of ownership – you drive outcomes, not just tasks; Ability to manage multiple customers and priorities; Structured, proactive, and solution-oriented mindset.

Qualifications

• Experience with GPU workload