Suggested rewrite: Led a cross-functional initiative that improved [business outcome] by [measurable result], demonstrating experience relevant to this role...
Principal Solutions Architect, Japan
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- Remote from
- Japan
- Salary
- Undisclosed
- Department
- DevOps & Infrastructure
- Employment
- Full Time
- Experience
- Director
- Published
- Apply before
- 29 Nov 2026
- Listing views
- 56
- Application actions
- 1
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The role, at a glance.
Nebius is hiring a Principal Solutions Architect to lead technical presales and end-to-end solution delivery for strategic AI cloud customers in Japan. The role focuses on architecting GPU-accelerated ML training, inference, MLOps, Kubernetes, and distributed infrastructure solutions from discovery and proof of concept through production adoption. This senior individual contributor will advise executive and engineering stakeholders, influence product direction, and collaborate closely with Sales, Product, Engineering, and Support. The position also includes technical thought leadership, customer workshops, and mentoring other Solutions Architects. Candidates need deep AI/ML infrastructure expertise, strong customer-facing consulting skills, and fluency in both Japanese and English.
Role DNA
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5/5Autonomy Level
5/5Communication Load
5/5Salary analysis
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Core skills
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Sample interview questions
I would begin by identifying business objectives, model characteristics, data volumes, training schedules, performance targets, security requirements, and current infrastructure constraints. I would then map these requirements to a reference architecture covering GPU selection, storage throughput, networking, orchestration, observability, cost controls, and operational ownership. The outcome would be a prioritized adoption plan and measurable success criteria for a proof of concept.
I would separate training and inference concerns while standardizing identity, networking, secrets, observability, artifact storage, and CI/CD workflows. The design would use Infrastructure as Code, scalable GPU node pools, workload scheduling and quota controls, model registry integration, automated deployment pipelines, and monitoring for infrastructure, model performance, and cost. I would validate reliability, rollback procedures, security controls, and service-level objectives before production rollout.
I assess GPU utilization, interconnect bandwidth and topology, storage I/O, data-loading efficiency, batch sizing, precision strategy, communication overhead, framework configuration, and checkpoint behavior. I use profiling data to identify whether the bottleneck is compute, memory, network, or input pipeline throughput. Recommendations are then validated through controlled benchmarks against agreed training-time and cost targets.
I first clarify the customer outcome, technical requirements, urgency, and acceptable alternatives. I work with Product and Engineering to determine whether a supported architecture, workaround, or scoped proof of concept can address the need without creating unsupported operational risk. I communicate trade-offs transparently to the customer and provide structured evidence to help internal teams prioritize the product gap.
For executives, I focus on business outcomes, risk, adoption milestones, cost drivers, and the decisions required to proceed. For platform engineers, I provide implementation detail such as system diagrams, sizing assumptions, Kubernetes configuration, security boundaries, performance testing, and operational runbooks. In both cases, I make the assumptions and success metrics explicit so that technical and business stakeholders remain aligned.
About this role.
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.
The role
We are seeking an experienced, customer-obsessed Solutions Architect to lead technical engagement with Nebius’ most strategic customers across multiple industry segments. This is a senior, high-impact role focused on complex presales, large-scale ML workloads, and end-to-end customer solution ownership — from early discovery through production adoption.
As a Principal Solutions Architect, you will act as a trusted technical partner for executive stakeholders, AI/ML leaders, and platform teams. You will shape solution strategy, drive complex PoCs, influence product direction, and ensure successful adoption of Nebius AI cloud for mission-critical ML/AI workloads.
As a core member of our founding Japan business team, you will have the opportunity to help shape the foundations of our culture and operations while working remotely and being based in the Greater Tokyo Area.
Your responsibilities will include:
- Own end-to-end technical presales and solution delivery for a diverse portfolio of strategic customers including AI-native and digital-native companies, strategic and large enterprises, and government organizations, from initial discovery through PoC, architecture design, and production readiness.
- Serve as a trusted technical advisor to senior customer stakeholders (CTO, Head of ML, Platform Engineering, AI Infrastructure teams).
- Lead complex ML/AI infrastructure and MLOps architectures, including large-scale training and inference workloads on GPU-accelerated cloud platforms.
- Design, validate, and document reference architectures, Infrastructure-as-Code solutions, and best-practice deployment patterns using Nebius AI.
- Drive and execute advanced PoCs, workshops, architecture reviews, and executive-level presentations to demonstrate value and accelerate customer adoption.
- Partner closely with Sales, Product, Engineering, and Support to represent real-world customer requirements and influence product roadmap decisions.
- Act as a single point of technical authority for key customer scenarios across internal teams (product, support, marketing).
- Support strategic marketing initiatives including conferences, hackathons, webinars, customer case studies, and technical thought leadership.
- Mentor and provide technical leadership to other Solutions Architects, helping raise the overall technical bar of the organization.
We expect you to have:
- 10+ years of experience in senior technical roles such as Solutions Architect, Systems Architect, ML Platform Engineer, or similar — with significant customer-facing responsibilities.
- Proven track record of end-to-end delivery of complex presales engagements, including discovery, solution design, PoCs, and production transition.
- Deep hands-on experience with large-scale ML-based workloads, including GPU training and inference at scale.
- Strong expertise in cloud infrastructure and MLOps, including Kubernetes-based platforms and distributed systems.
- Solid hands-on experience with Infrastructure as Code and configuration management (Terraform, Ansible), and strong Python skills.
- Deep understanding of GPU computing stacks for ML/AI workloads (drivers, CUDA, libraries, performance optimization).
- Exceptional communication skills — able to clearly articulate complex technical concepts to both technical and executive audiences.
- A highly customer-centric mindset with the ability to balance customer needs, technical feasibility, and product strategy.
- Fluency in Japanese and English, with the ability to communicate effectively with customers and stakeholders in both languages.
It will be an added bonus if you have:
- Prior experience as a Senior AI/ML Specialist Solutions Architect, Technical ML Product Manager, or in a similar senior AI/ML-focused role.
- Hands-on experience with HPC and ML orchestration frameworks (e.g., Slurm, Kubeflow).
- Practical experience with deep learning frameworks such as PyTorch and TensorFlow.
- Strong understanding of the cloud ML ecosystem across major providers (NVIDIA, AWS, Azure, Google Cloud).
- Experience influencing product direction based on customer feedback and real-world usage patterns.Experience leading and contributing to end-to-end large scale ML deployment projects on all layers of the stack.
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.
Annual salary information is not provided for this position. Explore salary ranges for similar roles in our Salary Directory ›
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