Senior Customer AI Engineer - Token Factory

Nebius is transforming cloud infrastructure for the global AI economy by building a full-stack platform that enables developers and enterprises to train models and deploy them to production without the overhead of maintaining large in-house infrastructure. Listed on Nasdaq and headquartered in Amsterdam, the company operates R&D hubs across Europe, North America, and Israel, with a team of over 1,500 engineers specializing in GPU orchestration, inference optimization, and applied AI systems.

The Token Factory team at Nebius is seeking a Senior Customer AI Engineer to guide enterprise customers through the critical transition from proof-of-concept to production-scale AI deployments. This role bridges engineering, delivery, and customer success, working directly with customer teams and internal product groups to ensure reliable, high-performing, and cost-efficient workloads run smoothly on Nebius infrastructure.

What you'll do

• Own the end-to-end production journey for customers, managing the transition from initial proof-of-concept through to scaled, stable deployments while driving time-to-value
• Monitor and optimize customer workload performance across latency, throughput, cost efficiency, and reliability, identifying bottlenecks before they impact production
• Work as a trusted technical advisor to customer engineering teams, providing guidance on best practices, system architecture optimization, and troubleshooting complex technical challenges
• Serve as the primary technical contact for production incidents and issues, coordinating resolution across internal teams while maintaining clear communication during high-pressure situations
• Gather feedback from real-world customer deployments and provide structured recommendations to Product and Infrastructure teams to drive platform improvements
• Identify opportunities to expand usage and optimize configurations, translating technical findings into actionable solutions for customers

What you'll bring

• Hands-on experience with inference frameworks such as vLLM, TensorRT, or equivalent technologies
• Strong foundational knowledge of cloud infrastructure, distributed systems, and high-load application design
• Practical understanding of AI and ML workloads, particularly large language models and inference optimization
• Demonstrated ability to troubleshoot complex system performance issues and reason about infrastructure bottlenecks
• Experience working directly with technical customers including engineers and machine learning teams, with excellent communication skills for explaining sophisticated concepts clearly
• Strong ownership mindset with the ability to manage multiple customers and shifting priorities in a proactive, structured manner

Nice to have

• Background with GPU workloads or AI infrastructure systems
• Previous experience in solutions engineering, site reliability engineering, or technical support roles within B2B environments

What they offer

• Competitive compensation
• Career growth and learning opportunities in a fast-moving AI infrastructure environment
• Flexibility and real ownership over outcomes
• Opportunity to work on impactful AI projects with an international team

Remote work from Singapore is available for this full-time position.