Account Solution Architect (Financial Services)

Join CoreWeave, the AI-first cloud designed for AI workloads. As an Account Solutions Architect for Financial Services, you'll be the technical partner for existing financial services customers, helping them solve real-world problems and deepen their platform adoption. You'll work closely with Account Managers, Specialist Field Engineers, and customer teams to ensure maximum value from CoreWeave. This role is ideal for customer-focused AI practitioners with experience in financial services and a passion for scaling AI workloads in production.

• Establish and maintain technical relationships with existing financial services customers, serving as a trusted advisor and technical partner.
• Collaborate with cross-functional teams, including Sales, Support, Product, and Engineering, to drive customer success and deepen platform adoption.
• Identify and drive expansion opportunities within customer accounts, working closely with Account Managers on the commercial motion.
• Familiarity with running AI workloads least one major cloud platform (AWS, GCP, or Azure)
• Experience
• Experience working with financial services customers, such as quantitative trading firms, hedge funds, asset managers, banks, or other enterprise finance organizations, with an understanding of their unique technical, operational, and business-critical requirements
• Demonstrated ability to break down and solve complex, often novel, technical problems with enterprise customers
• Hands-on experience training, fine-tuning, evaluating, and deploying deep learning models, including modern LLM architectures
• Proficiency in Python
• Experience designing and deploying production LLM-powered applications for customer use cases
• 4+ years of relevant experience in a solutions engineer, AI-oriented solutions consultant, or technical field engineering role
• Excellent written and verbal communication and presentation skills, with the ability to translate technical concepts for both engineering and executive audiences
• 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)
• Wondering if you’re a good fit? We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren't a 100% skill or experience match. Here are a few qualities we’ve found compatible with our team. If some of this describes you, we’d love to talk
• You'd rather show than tell — you build the demo or PoC instead of just pitching it
• You're genuinely curious about your customers' work — what they're building, what's getting in their way, what success looks like for them
• You get excited by empty whiteboards —new customers, novel problems, new playbooks for AI natives