Senior Sales Engineer - Token Factory

Details

Nebius is building a full-stack AI cloud platform for developers and enterprises, supporting workloads from data and model training through production deployment. The company operates globally, with expertise across GPU orchestration, inference optimization, compute, storage, networking, and applied AI.

This role supports a high-performance AI inference platform for developer-native teams running latency- and cost-sensitive workloads at scale. The Senior Sales Engineer will serve as a technical partner to customers and a force multiplier for Sales and Engineering, shaping complex AI workloads from discovery through production feasibility validation. The role focuses on technical rigor, economic viability, scalable architecture, engineering prioritization, product evolution, and customer trust.

Responsibilities

Strategic Technical Discovery

• Lead deep technical discovery with engineering teams and technical founders.
• Understand model requirements, traffic expectations, latency constraints, GPU economics, and system dependencies.
• Translate customer ambitions into production-feasible architectures.
• Identify hidden technical risks early.

Commercial Acceleration

• Partner closely with Sales on strategic deals.
• Influence deal strategy through architectural clarity.
• Prevent misaligned commitments before engineering resources are allocated.
• Increase proof-of-concept-to-production conversion by ensuring technical realism.

Proof-of-Concept Architecture and Validation

• Define measurable success criteria, including latency, time to first token (TTFT), throughput, and cost envelope.
• Classify workload complexity and determine the required optimization depth.
• Align appropriate resources, including ML Solution Architects, Engineering, and GPU capacity.
• Drive structured go/no-go decisions.
• Prevent uncontrolled customization and hidden research and development work.

Pattern Recognition and Platform Leverage

• Identify recurring configuration patterns across customers.
• Quantify demand for advanced optimizations such as quantization and speculative decoding.
• Surface structured insights to Product and Engineering.
• Help evolve platform capabilities based on real workload data.

Requirements

• Deep understanding of AI inference systems and GPU-backed infrastructure.
• Experience with large language model (LLM) workloads and performance-sensitive environments.
• Experience with inference frameworks and libraries such as vLLM, SGLang, and TensorRT-LLM.
• Ability to reason about latency, throughput, cost, and architecture trade-offs.
• Strong customer presence with engineering-first organizations.
• Ability to challenge assumptions and push back constructively.
• Commercial awareness and understanding that engineering time is a strategic resource.

Preferred Technical Stack

• Programming languages: Python
• Inference frameworks and libraries: vLLM, SGLang, TensorRT-LLM, OpenAI SDKs, Anthropic SDKs
• Agentic pipeline frameworks: LangChain, LangSmith, smolagents, or equivalent
• API and web frameworks: FastAPI, Flask
• MLOps and DevOps tools: Kubernetes, Docker, Git
• Cloud platforms: AWS, including SageMaker and Bedrock; GCP, including Vertex AI; Azure, including Azure ML

Success Criteria

• Strategic deals are technically sound before Engineering engagement.
• Proofs of concept are clearly scoped and economically justified.
• Engineering capacity is allocated predictably.
• Conversion to production improves.
• Customers view the Sales Engineer as a trusted architectural advisor.

Benefits

• 100% company-paid medical, dental, and vision coverage for employees and families.
• 401(k) plan with up to a 4% company match and immediate vesting.
• Paid parental leave: 20 weeks for primary caregivers and 12 weeks for secondary caregivers.
• Remote work reimbursement of up to $85 per month for mobile and internet.
• Company-paid short-term disability, long-term disability, and life insurance.
• Career growth and learning opportunities.
• Flexibility and ownership.
• Collaborative and innovative culture.
• Opportunity to work on impactful AI projects.
• International environment and talented teams.

Applicants must be authorized to work in the United States and must provide proof of employment eligibility as a condition of hire. Nebius is an equal opportunity employer and provides accommodations during the application process when needed.