Senior Customer AI Engineer - Token Factory

About Nebius:

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.

The role 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.

Your responsibilities will include:

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

We expect you to have:

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

It will be an added bonus if you have:

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

Key employee benefits in the US:

Health insurance: 100% company-paid medical, dental, and vision coverage for employees and families. 401(k) plan: Up to 4% company match with immediate vesting. Parental leave: 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers. Remote work reimbursement: Up to $85/month for mobile and intern...