Solutions Architect

Weights & Biases Weights & Biases · Data AI · Washington, DC · Global Field Organization

Solutions Architect for CoreWeave Federal, focusing on designing and deploying AI workloads for U.S. government agencies within regulated environments. This role requires expertise in AI/ML model deployment, agentic applications, and compliance with federal standards like FedRAMP and DoD Impact Levels.

What you'd actually do

  1. Serve as the named technical partner for federal customers across CoreWeave's full platform
  2. Provide technical guidance on running AI workloads in regulated environments, including FedRAMP, DoD Impact Levels (IL2–IL6), and emerging AI-specific federal standards
  3. Represent the voice of the federal customer internally — distilling requirements, compliance gaps, and federal use case patterns back to Product, Security, and Engineering
  4. Build reference architectures and enablement content for federal engagements, raising the technical bar of the federal field organization as it scales

Skills

Required

  • U.S. Citizenship and an active U.S. government security clearance
  • 5+ years in a solutions engineer, solutions architect, or technical field engineering role
  • at least 3 years supporting federal customers
  • Strong Python proficiency
  • hands-on experience training, fine-tuning, evaluating, and deploying modern deep learning models, including LLMs
  • experience designing and deploying production agentic applications for real customer use cases
  • Working knowledge of federal cybersecurity frameworks and authorization processes
  • familiarity running AI workloads on at least one major cloud platform (AWS/GovCloud, Azure/Government, or GCP/Government)

Nice to have

  • Active TS/SCI clearance, ideally with a current CI or Full Scope Polygraph
  • Familiarity with deep learning frameworks (PyTorch)
  • modern LLM stack (vLLM, LangChain, LlamaIndex)
  • Working knowledge of cloud infrastructure for AI workloads, including GPU compute, high-performance networking, and storage
  • Experience using Slurm or Kubernetes for ML job orchestration, especially in air-gapped or classified environments
  • Background in ML Engineering, AI Engineering, MLOps, or LLMOps with public sector or defense customers

What the JD emphasized

  • active U.S. government security clearance (Secret minimum; TS/SCI strongly preferred)
  • design and deploying production agentic applications for real customer use cases
  • Working knowledge of federal cybersecurity frameworks and authorization processes

Other signals

  • AI Hyperscaler
  • AI workloads in regulated environments
  • design and deploy production agentic applications