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.
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 what we commit to with customers is scalable, efficient, and aligned with platform strategy.
We are looking for a Presales Architect to become a foundational technical partner to our customers and a force multiplier for Sales and Engineering. You will shape complex AI workloads from first 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
- Customer trust at scale
You’re welcome to work remotely from the United States.
Your responsibilities will include:
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
We expect you to have:
- 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 – you understand 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 / 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
Key employee benefits in the 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
We offer competitive salaries, ranging from $152k - 228k base + RSU's and performance bonus's.
Benefits & Perks:
- Competitive compensation
- Career growth and learning opportunities
- Flexibility and work-life balance
- Collaborative and innovative culture
- Opportunity to work on impactful AI projects
- International environment and talented teams
What's it like to work at Nebius:
Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI
Equal Opportunity Statement:
Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law.
Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire.
If you need accommodations during the application process, please let us know.
Skills Required
- Deep understanding of AI inference systems and GPU-backed infrastructure
- Experience with LLM workloads and performance-sensitive environments
- Strong customer presence with engineering-first organizations
What We Do
Cloud platform specifically designed to train AI models
