Senior Sales Engineer

at Nebius

📍 United States

USD 152,000-228,000 per year

SENIOR

✅ Remote

Used Tools & Technologies

Machine Learning

Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

Docker @ 4 Kubernetes @ 4 DevOps @ 4 Python @ 4 GCP @ 4 MLOps @ 4 Vertex AI @ 4 AWS @ 4 Azure @ 4 FastAPI @ 4 Flask @ 4 Git @ 4 API @ 4 LLM @ 4 Cloud Computing @ 4 GPU @ 4 AI @ 4 vLLM @ 4 TensorRT @ 4 LangChain @ 4 SGLang @ 4

Details

Nebius is leading a new era in cloud computing to serve the global AI economy. We create tools and resources to help customers solve real-world challenges and transform industries without massive infrastructure costs or large in-house AI/ML teams. Headquartered in Amsterdam and listed on Nasdaq, Nebius has R&D hubs across Europe, North America, and Israel, and a team of over 800 employees including more than 400 engineers.

Role overview

We are building a high-performance AI inference platform for developer-native teams running latency- and cost-sensitive workloads at scale. In AI infrastructure, PoC success does not always guarantee production success — this role exists to ensure that commitments to customers are scalable, efficient, and aligned with platform strategy.

As a Senior Sales Engineer you will be a foundational technical partner to customers and a force multiplier for Sales and Engineering. You will shape complex AI workloads from discovery through production feasibility validation, ensuring technical rigor, economic viability, and scalable architecture decisions. You will operate at the intersection of customer ambition, engineering reality, and commercial growth, influencing revenue quality, engineering focus, product evolution, and customer trust at scale.

You are welcome to work remotely from the United States.

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 ambition into production-feasible architecture
Identify hidden technical risks early

Commercial Acceleration

Partner tightly with Sales on strategic deals
Influence deal strategy through architectural clarity
Prevent misaligned commitments before engineering allocation
Increase PoC-to-production conversion by ensuring technical realism

PoC Architecture & Validation

Define measurable success criteria (latency, TTFT, throughput, cost envelope)
Classify workload complexity and required optimization depth
Align appropriate resources (ML Solution Architects, engineering, GPU capacity, etc.)
Drive structured Go / No-Go decisions
Prevent uncontrolled customization or hidden R&D

Pattern Recognition & Platform Leverage

Identify recurring configuration patterns across customers
Quantify demand for advanced optimizations (quantization, speculative decoding, etc.)
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 LLM workloads and performance-sensitive environments
Experience with inference frameworks and libraries (e.g., vLLM, SGLang, TensorRT-LLM)
Ability to reason about latency, throughput, cost, and architecture tradeoffs
Strong customer presence with engineering-first organizations
Comfort challenging assumptions and pushing back constructively
Commercial awareness — understanding that engineering time is a strategic resource

Preferred technical stack

Programming languages: Python
Frameworks and libraries: vLLM, SGLang, TensorRT-LLM, OpenAI/Anthropic SDKs
Frameworks for agentic pipelines: LangChain, Langsmith, smolagents or equivalent
API and web frameworks: FastAPI, Flask
MLOps and DevOps tools: Kubernetes (K8s), Docker, Git
Cloud platforms: AWS (SageMaker, Bedrock), GCP (Vertex AI), Azure (Azure ML)

What success looks like

Strategic deals are technically sound before engineering engagement
PoCs are clearly scoped and economically justified
Engineering capacity is allocated predictably
Conversion to production improves
Customers view you as a trusted architectural advisor

Benefits (US)

Health insurance: 100% company-paid medical, dental, and vision coverage for employees and families
401(k) plan: Up to 4% company match with immediate vesting
Parental leave: 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers
Remote work reimbursement: Up to $85/month for mobile and internet
Disability & life insurance: Company-paid short-term, long-term and life insurance coverage

Compensation

Base salary range: $152,000 - $228,000 base + RSUs and performance bonuses.

What we offer

Competitive salary and comprehensive benefits package
Opportunities for professional growth within Nebius
Flexible working arrangements
A dynamic and collaborative work environment that values initiative and innovation