Account Solution Architect

Weights & Biases Weights & Biases · Data AI · New York, NY · Global Field Organization

This role is for an Account Solutions Architect at CoreWeave, an AI-focused cloud provider. The architect will be the technical partner for prospective customers, designing demos, leading PoCs, and advising on best practices for AI workloads, including training, fine-tuning, evaluating, and deploying deep learning models and LLM-powered applications. The role requires strong Python skills, experience with major cloud platforms, and the ability to solve complex technical problems.

What you'd actually do

  1. Own the technical relationship with every CoreWeave customer.
  2. Work hands-on with some of the most advanced AI teams in the world as they build, train, deploy, and scale their workflows.
  3. Design custom demos, leading proofs of concept (PoCs) end-to-end, and acting as a trusted advisor on best practices from the first technical conversation through production and expansion.
  4. Partner closely with Account Executives on the commercial motion, with Specialist Field Engineers for deep domain expertise, and act as a trusted advisor on best practices for AI workloads.
  5. Represent the voice of the customer internally and help shape the product roadmap based on what you see in the field.

Skills

Required

  • 4+ years of relevant experience in a solutions engineer, AI-oriented solutions consultant, or technical field engineering role
  • Proficiency in Python
  • Hands-on experience training, fine-tuning, evaluating, and deploying deep learning models, including modern LLM architectures
  • Experience designing and deploying production LLM-powered applications for customer use cases
  • Familiarity with running AI workloads least one major cloud platform (AWS, GCP, or Azure)
  • Demonstrated ability to break down and solve complex, often novel, technical problems with enterprise customers
  • Excellent written and verbal communication and presentation skills

Nice to have

  • Working knowledge of cloud infrastructure for AI workloads, including GPU compute, high-performance networking, and storage
  • Familiarity one or more deep learning frameworks (PyTorch) and modern LLM stack (VLLM, langchain / LlamaIndex)
  • Experience using Slurm or Kubernetes for ML job orchestration
  • Experience with hyperparameter optimization and experiment tracking tools
  • Background in ML Engineering, AI Engineering, MLOps, or LLMOps
  • Prior experience in a technical pre-sales or solutions architecture role focused on net-new logos or greenfield accounts
  • Familiarity with high-performance GPU infrastructure (e.g., NVIDIA H100/H200/B200, InfiniBand networking, parallel file systems)

What the JD emphasized

  • Hands-on experience training, fine-tuning, evaluating, and deploying deep learning models, including modern LLM architectures
  • Experience designing and deploying production LLM-powered applications for customer use cases
  • customer-focused AI practitioners
  • novel technical problems
  • novel problems

Other signals

  • AI-first cloud platform
  • purpose-built for AI workloads
  • work hands-on with advanced AI teams
  • design custom demos
  • leading proofs of concept (PoCs) end-to-end
  • trusted advisor on best practices for AI workloads
  • designing and deploying production LLM-powered applications