CoreWeave
Solutions Architect
$165K–$220K
Washington, D.C. +1 · Full-time · Posted Jun 30, 2026
- Location
- Washington, D.C.
Washington, District of Columbia, United States - Experience
- 5+ years in solutions engineering, solutions architecture, or technical field engineering, including at least 3 years supporting federal customers.
- Visa sponsorship
- Requires U.S. citizenship and an active U.S. government security clearance of Secret minimum; must be eligible to obtain and maintain higher clearances. Export-controlled information access requires meeting one of the stated U.S. person, export authorization, or eligibility criteria.
About the job
Serves as the technical partner for U.S. federal customers, designing compliant AI workloads and leading technical engagements across CoreWeave’s platform.
What you'll do
- Advise federal customers on AI workloads in regulated environments and applicable federal standards.
- Lead proofs of concept and develop reference architectures and enablement content for federal engagements.
- Represent customer requirements and compliance gaps to Product, Security, and Engineering.
What they ask for
- U.S. citizenship and an active U.S. government security clearance of at least Secret; must be eligible to obtain and maintain higher clearance levels.
- Strong Python proficiency and hands-on experience training, fine-tuning, evaluating, and deploying deep learning models, including LLMs; experience deploying production agentic applications.
- 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 PyTorch, vLLM, LangChain, LlamaIndex, Slurm, or Kubernetes; AI infrastructure or public-sector ML/AI engineering experience.
Pay
USD 165,000 to USD 220,000 (base salary)
Tools
Python, LLMs, AWS/GovCloud, Azure/Government, GCP/Government, PyTorch, vLLM, LangChain
AI focus
Hands-on work training, fine-tuning, evaluating, and deploying deep learning models and LLMs, as well as designing and deploying production agentic applications for federal missions.
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