Account Solutions Architect - Greenfield - DACH

What You’ll Do:

The infrastructure powering the AI era doesn’t sell itself, and the customers building on it don’t want to be sold to. They want a peer. You’ll work as part of a focused three-person team alongside one Account Executive and one Account Manager, together responsible for landing new accounts and expanding within them across the region. The customers you’ll work with are AI labs, research institutions, and enterprises running some of the most demanding GPU workloads in the world. This is a role for someone who shows up with substance, who can hold a real conversation about model training and MLOps tooling in the morning and cluster networking in the afternoon, and who finds the space between infrastructure and application more interesting than either on its own.

About the Role:

As an Account Solution Architect covering Northern EMEA, you’ll move across the full stack depending on what the customer needs, from ML training workflows and MLOps platforms like Weights & Biases to bare metal GPU infrastructure and physical AI deployments. This isn’t a role built around a single layer of the stack, but the majority of your conversations will live in the ML layer. You’ll be expected to go deeper than most when the infrastructure conversation demands it, while staying commercially aware enough to support both new logo pursuits and in-flight account expansion. This role requires up to 40% travel.

In this role, you will:

• Cover Northern EMEA, with a focus on the Nordics and Benelux regions (Sweden, Norway, Denmark, Finland, Netherlands, Belgium, and Luxembourg).
• Work closely with one Account Executive and one Account Manager as a dedicated three-person unit, supporting the full land and expand motion across the region.
• Lead technical discovery with prospects and existing customers to understand model training requirements, MLOps workflows, and infrastructure constraints.
• Design and present solutions spanning ML infrastructure, GPU compute, storage, networking, Kubernetes-based orchestration, and MLOps tooling.
• Run proof-of-concept engagements and architecture reviews, and see them through to a decision.
• Act as the internal voice of the customer, feeding technical requirements and product gaps back to Engineering and Product.
• Maintain clear documentation of customer architectures, solution designs, and outstanding technical questions.

Who You Are:

• 3+ years in a pre-sales, solutions engineering, or solutions architecture role, ideally with a focus on AI/ML platforms, cloud infrastructure, or HPC.
• Strong working knowledge of ML training and inference workflows - you understand how models are built, optimized, and deployed, not just where they run.
• Hands-on familiarity with MLOps platforms and the tooling AI teams use day-to-day, including experiment tracking, pipeline orchestration, and model serving.
• Experience with AI frameworks such as PyTorch, TensorFlow, or JAX.
• Comfortable going below the SaaS layer when the conversation demands it - GPU topology, network fabric, and cluster architecture shouldn’t be unfamiliar territory.
• Hands-on experience with Kubernetes and containerized workloads at scale.
• Strong communication skills - you can adjust your register from a research engineer to a VP of Infrastructure without losing credibility at either end.
• Experience managing multiple concurrent opportunities across a geographic territory.
• Fluency in English required; proficiency in Dutch, Swedish, Norwegian, Danish, or Finnish is a plus.

Preferred:

• Familiarity with NVIDIA GPU architectures (H100, A100, H200) and the software stack around them: CUDA, NCCL, cuDNN.
• Working knowledge of high-performance networking concepts: InfiniBand, RDMA, RoCE, TCP/IP.
• Background working directly with AI labs, research institutions, or enterprise ML teams.
• Exposure to physical AI use cases and the infrastructure requirements they bring.
• Experience with Salesforce, Jira, Confluence, or similar tools.

Wondering if you’re a good fit? We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams - even if you aren’t a 100% skill or experience match. Here are a few qualities we’ve found compatible with our team. If some of this describes you, we’d love to talk.

• You’re comfortable going one layer deeper than the demo - whether that’s a networking topology, a training job that won’t converge, or a rack layout question from a facilities team.
• You’ve worked across more than one layer of the stack and find the intersections more interesting than any single discipline.
• You thrive in a fast-moving environment and take ownership of your region like it’s your own business.
• You’re a natural collaborator who makes the people around you - including your AE and AM - better at their jobs.

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast! We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values:

• Be Curious at Your Core
• Act Like an Owner
• Empower Employees
• Deliver Best-in-Class Client Experiences
• Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and enables the development of innovative solutions to complex problems. As we get set for takeoff, the growth opportunities within the organization are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us!

The starting salary will be determined by job-related knowledge, skills, experience, and the market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).