Partner Solutions Architect

Remote from: Europe
Annual salary: Undisclosed
Salary information is not provided for this position. Check our Salary Directory to estimate the average compensation for similar roles.
Department: Software Engineering
Employment type: Full Time,
Job posted: 21 Jul 2026
Apply before: 21 Aug 2026
Experience level: Senior
Views / Applies: 46 / 3

Nebius is the AI cloud company, delivering a unified platform that spans the complete AI journey from data and model training and tuning to production runtime and deployment.

Computer Software
2023

Actively Hiring

AI Summary

Nebius is seeking a Partner Solutions Architect to act as the technical interface between the company and its strategic technology partners, including data platforms, MLOps vendors, and AI frameworks. This hands-on role involves designing and building integrated solutions, reference implementations, and providing technical leadership to ensure joint customer success. The ideal candidate has 5+ years in solutions architecture, deep cloud infrastructure knowledge, and hands-on experience with GPU-accelerated AI/ML workflows. Nebius offers a fast-paced, low-bureaucracy environment with opportunities for growth and impact. The position can be based in Amsterdam or remotely from any EU country.

Role DNA

Job Complexity

Easy Hard

Pace & Pressure

Relaxed Fast-paced

Autonomy Level

Guided Full Ownership

Communication Load

Independent Highly Collaborative

AI Insight The role demands a broad skill set spanning cloud infrastructure, AI/ML workflows, and integration architecture, plus the ability to manage partner relationships and complex customer deployments, making it challenging but not extreme.

Salary Analysis

AI Insight The job listing does not specify a salary, but the typical US market range for a Partner Solutions Architect is $130,000–$220,000. The estimated median of $175,000 is competitive considering the required expertise and responsibilities.

Core Skills Required

Solutions Architecture Cloud Infrastructure GPU Computing AI/ML Partner Engineering Integration Architecture Python IaC MLOps Technical Pre-sales

Cover Letter Sample

Dear Hiring Manager,

I am writing to express my strong interest in the Partner Solutions Architect role at Nebius. With over 7 years of experience in cloud infrastructure and solutions architecture, including a focus on AI/ML workflows, I am confident in my ability to drive technical partnerships and deliver impactful integrations. At my previous role with a major cloud provider, I led the design and deployment of GPU-accelerated training pipelines and built reference architectures that enabled joint customer success.

I am particularly drawn to Nebius’s commitment to reducing complexity for AI developers and its fast-moving, engineer-driven culture. My hands-on experience with Python, IaC tools, and integration patterns (APIs, security, observability) aligns perfectly with the responsibilities outlined. I thrive in collaborative, autonomous environments and look forward to contributing to Nebius’s growth in the AI cloud space.

Thank you for considering my application. I look forward to discussing how I can add value to your team.

Sincerely,
[Your Name]

Sample Interview Questions

Can you describe a time when you designed a complex integration between a cloud platform and a third-party AI/ML tool? What challenges did you face and how did you overcome them?

In my previous role, I led the integration of a customer's MLOps pipeline with our GPU cloud. The main challenge was ensuring data security across different compliance zones. I implemented a VPC peering setup with encrypted data transfer and worked with the partner to align their API usage with our authentication protocols. We also built a reference architecture that reduced deployment time by 40%.

How would you approach enabling a new partner’s engineering team to work effectively with Nebius’s infrastructure?

I would start by understanding their current workflows and pain points. Then, I'd create tailored technical documentation and hands-on demos using common patterns like training, inference, and MLOps. I'd also establish a regular cadence of office hours and provide a sandbox environment for testing. Finally, I'd ensure clear escalation paths for any issues.

Explain your experience with GPU-accelerated AI/ML workflows, specifically in training or inference optimization.

I have worked on distributed training of large language models using frameworks like PyTorch and TensorFlow on multi-GPU clusters. For inference, I optimized model serving using NVIDIA Triton and vLLM, achieving sub-10ms latency. I also fine-tuned models for specific use cases, leveraging mixed precision and gradient checkpointing to reduce memory usage.

Tell us about a time you had to convince a non-technical stakeholder to adopt a technical solution. How did you communicate the value?

I once presented a migration plan to a VP of Product. Instead of technical details, I focused on business outcomes: reduced time-to-market, cost savings, and improved scalability. I used analogies and ROI calculations to show how the integration would enable faster AI model deployment. The stakeholder approved the plan and we saw a 30% reduction in operational costs.

How do you stay current with rapidly evolving AI/ML and cloud technologies?

I regularly read research papers on ArXiv, attend conferences like re:Invent and KubeCon, and participate in open-source projects. I also contribute to internal knowledge bases and run experiments with new tools like Ray or Kubernetes operators for GPU scheduling. This helps me bring innovative ideas to partner engagements.

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.

Customer experience

Customer experience at Nebius AI Cloud involves tackling customers’ challenges and directly impacting their success by solving real-world AI and ML problems at massive GPU cloud scale. You’ll not only resolve issues, but play a key role in shaping clients’ business success by optimizing their AI solutions.

Working with advanced GPUs such as H200, B200 and GB200, as well as modern ML frameworks, you’ll influence the development of the Nebius AI Cloud and gain experience at the intersection of infrastructure and AI. With minimal bureaucracy, you’ll have the freedom to innovate, take ownership and drive change. Opportunities for growth are abundant in this vibrant and supportive professional community.

The role

We are looking for a Partner Solutions Architect to serve as the technical interface between Nebius and our strategic technology partners, ranging from data platforms and MLOps vendors to AI frameworks and ISVs that build on GPU infrastructure.
This is a hands-on engineering and integration role. You will design and develop integrated solutions, build reference implementations, enable partner engineering teams, and ensure joint customers succeed with combined offerings. You will influence Nebius’ product roadmap and drive deep technical collaboration across partner ecosystems.

You’re welcome to work from our office in Amsterdam or remotely from any EU country.

Your responsibilities will include:

Own the technical relationship with strategic partners as the primary interface to Nebius engineering and product
Design and architect high-impact integration solutions, delivering clear joint customer value
Build and maintain reference implementations and production-grade integrations
Define enterprise-ready integration patterns (networking, security, compliance, observability)
Translate partner and customer feedback into actionable product and roadmap requirements
Enable partner teams through technical documentation, training, and demo environments
Provide technical leadership in joint customer deployments, architecture reviews, and complex troubleshooting

We expect you to have:

5+ years in solutions architecture, partner engineering, or technical pre-sales at cloud or data platform companies
Strong expertise in cloud infrastructure
Hands-on experience with GPU-accelerated AI/ML workflows (training, inference, MLOps)
Proven background in integration architecture (API design, data pipelines, security, observability)
Experience with Python and IaC tools
Excellent communication skills with the ability to engage technical and non-technical stakeholders

It will be an added bonus if you have:

Track record of building or scaling partner technical programs or ecosystems
Experience working with or at Snowflake, Databricks, AWS, Azure, or GCP
Background in ML lifecycle (training pipelines, fine-tuning, inference optimization, RAG

Benefits & Perks:

Competitive compensation
Career growth and learning opportunities
Flexibility and ownership
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.

Apply now >