Technical Account Manager

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 Technical Account Manager (TAM) 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.

• 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

• 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.), 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

• 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