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 Singapore . 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: o performance (latency, throughput) o cost efficiency o 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.) • 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 Benefits & Perks: • 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 t