Account Solution Architect
Listed on 2026-06-07
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IT/Tech
AI Engineer, Cloud Computing
Core Weave is the Essential Cloud for AI. Built for pioneers by pioneers, Core Weave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, Core Weave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, Core Weave became a publicly traded company (Nasdaq: CRWV) in March 2025.
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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.
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 & BIAS 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.
- 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.
- 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, Tensor Flow, 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.
- Familiarity with NVIDIA GPU architectures (H100, A100, H200) and the software stack around them: CUDA, NCCL, cuDNN.
- Working knowledge of high-performance networking…
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