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Nebius is a Nasdaq-listed AI cloud infrastructure company building a full-stack platform for data, model training, and production deployment. The company operates globally with R&D hubs across Europe, North America, and Israel, and employs 1,500+ engineers with deep expertise in hardware, software, and AI.
You will join the Token Factory team as a Senior Customer AI Engineer, sitting at the intersection of engineering, delivery, and customer success. Your mission is to help customers transition from proof-of-concept to production and scale their AI workloads reliably on Nebius infrastructure.
This is not a pure sales, support, or solution architecture role. Instead, you will own the production journey end-to-end: leading PoC-to-production transitions, ensuring workloads are deployed stably and scalably, and driving time-to-value. You will work directly with customer engineering teams, Solution Architects, and internal Product/Infrastructure teams to deliver stable, performant, and cost-efficient deployments.
Key responsibilities include:
- Own the production journey from PoC through scaling, ensuring customer workloads are deployed, stable, and scalable
- Understand customer architectures and use cases; monitor and improve performance (latency, throughput), cost efficiency, and reliability
- Identify and resolve bottlenecks proactively
- Act as a trusted technical partner, providing guidance on best practices and optimization
- Serve as the primary technical contact for production issues; coordinate with internal teams to resolve incidents
- Communicate clearly during high-pressure situations
- Identify opportunities to optimize and expand usage; provide structured feedback to Product and Infrastructure teams
- Help shape better solutions based on real customer needs
You will be based in Singapore with full remote flexibility.
REQUIREMENTS:
- Practical knowledge of inference frameworks (e.g., vLLM, TensorRT, or similar)
- Solid understanding of cloud or infrastructure systems, distributed systems or high-load applications, and AI/ML workloads (LLMs, inference, etc.)
- Ability to troubleshoot and reason about system performance
- Experience working directly with technical customers (engineers, ML teams)
- Ability to communicate complex topics clearly and effectively
- Strong sense of ownership; you drive outcomes, not just tasks
- Ability to manage multiple customers and priorities
- Structured, proactive, and solution-oriented mindset
BONUS QUALIFICATIONS:
- Experience with GPU workloads or AI infrastructure
- Background in solutions engineering, SRE, or technical support in B2B environments
