Principal Solutions Architect, South Korea

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 Seoul 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 Korean 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.