Senior Customer AI Engineer - Token Factory

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)
Lead the transition from PoC to production
Ensure customer workloads are deployed, stable, and scalable
Drive time-to-production and time-to-value
Understand customer architectures and use cases
Monitor and improve:
- performance (latency, throughput)
- cost efficiency
- 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 a 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
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
Experience working directly with technical customers (e.g. engineers, ML teams)
Ability to communicate complex topics clearly and effectively
Strong sense of ownership – you drive outcomes, not just tasks
Ability to manage multiple customers and priorities
Structured, proactive, and solution-oriented mindset

Experience with GPU workloads or AI infrastructure
Background in solutions engineering, SRE, or technical support in B2B environments