Account Solution Architect

Weights & Biases Weights & Biases · Data AI · London, United Kingdom · Global Field Organization

Account Solution Architect for CoreWeave, focusing on AI/ML infrastructure and MLOps solutions for customers in Northern EMEA. The role involves technical discovery, solution design, proof-of-concept engagements, and acting as a customer advocate to internal teams. Requires strong knowledge of ML training/inference, MLOps platforms, and underlying infrastructure like GPUs, networking, and Kubernetes.

What you'd actually do

  1. Lead technical discovery with prospects and existing customers to understand model training requirements, MLOps workflows, and infrastructure constraints.
  2. Design and present solutions spanning ML infrastructure, GPU compute, storage, networking, Kubernetes-based orchestration, and MLOps tooling.
  3. Run proof-of-concept engagements and architecture reviews, and see them through to a decision.
  4. Act as the internal voice of the customer, feeding technical requirements and product gaps back to Engineering and Product.
  5. Maintain clear documentation of customer architectures, solution designs, and outstanding technical questions.

Skills

Required

  • Pre-sales, solutions engineering, or solutions architecture experience
  • Knowledge of ML training and inference workflows
  • Familiarity with MLOps platforms and tooling
  • Experience with AI frameworks (PyTorch, TensorFlow, JAX)
  • Experience with Kubernetes and containerized workloads
  • Strong communication skills
  • Experience managing multiple concurrent opportunities
  • Fluency in English

Nice to have

  • Familiarity with NVIDIA GPU architectures and software stack
  • Working knowledge of high-performance networking concepts
  • Background working directly with AI labs, research institutions, or enterprise ML teams
  • Exposure to physical AI use cases
  • Experience with Salesforce, Jira, Confluence
  • Proficiency in Dutch, Swedish, Norwegian, Danish, or Finnish

What the JD emphasized

  • 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.

Other signals

  • customer-facing technical role
  • designing and presenting solutions
  • ML infrastructure and MLOps tooling