Account Solution Architect - Financial Services

CoreWeave is The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at  www.coreweave.com . What You’ll Do: CoreWeave is the AI-first cloud where every layer, from compute and networking through orchestration, observability, and the broader AI tooling stack, is purpose-built for AI workloads. The Field Engineering team owns the technical relationship with every CoreWeave customer. We partner with Sales, Support, Product, and Engineering to deliver technical success across the full customer lifecycle. You’ll work hands-on with some of the most advanced AI teams in the world as they build, train, deploy, and scale their workflows. Greenfield is where we meet the next generation of those teams — net-new customers that haven’t yet built on CoreWeave. We hire technical, AI Solution Architects who want to operate the full stack, own customer relationships end-to-end, and grow on a visible technical ladder that recognizes customer impact above all. About the role: The Account Solutions Architect, Engaged, Financial Services is the named technical partner to existing financial services customers across CoreWeave’s full platform: infrastructure, Models, Weave, observability, and inference. You’ll work with some of the most sophisticated AI and compute-intensive organizations in the market, including quantitative trading firms, hedge funds, asset managers, and other financial institutions using AI, ML, and large-scale compute to drive business-critical outcomes. You’ll help these customers 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 they scale AI workloads in production. This includes understanding how financial services customers approach model development, research velocity, evaluation, production deployment, governance, performance, reliability, and infrastructure efficiency. 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 financial services customers 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 understand the demands of financial services environments and are excited to help leading quant, hedge fund, and enterprise finance teams 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. Experience 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 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. 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) Wondering if you’re a good fit? We believe in investing in our people, and value c