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 Europe.
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