Account Solutions Architect

Description:

The Account Solutions Architect, Engaged is the named technical partner to existing customers across CoreWeave’s full platform — infrastructure, Models, Weave, observability, and inference. You’ll help AI teams solve real-world problems by deepening platform adoption, identifying and driving expansion opportunities, strengthening relationships with key technical stakeholders, and serving as a trusted advisor as customers scale their AI workloads in production. You’ll partner closely with Account Managers on the commercial motion, with Specialist Field Engineers for deep domain expertise, and with customer teams to ensure they are getting maximum value from CoreWeave. You’ll represent the voice of the customer internally, surface product

feedback from the field, and proactively address technical blockers and business-critical needs to ensure customer success. This role is for customer-focused AI practitioners who are excited to help leading AI companies deepen their partnership with CoreWeave and scale the next generation of AI workloads in production.

Who You Are
 

• 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, with the ability to translate technical concepts for both engineering and executive audiences
   

Preferred: (if applicable)
 

• 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)