Description
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.
As a GTM Solution Specialist for Healthcare & Life Sciences, you open new market opportunities with the world's leading pharma, biotech, and healthcare organizations, and drive the initial adoption of CoreWeave's Essential AI cloud with the earliest customers building AI-native drug discovery and clinical programs.
In this role, you will:
- Own the commercial and technical strategy for net new customer wins in HCLS AI, where foundation model training, genomics and imaging pipelines, and regulated AI deployment are the primary buying triggers.
- Drive new business opportunities at pharmaceutical companies, techbio and biotech firms, medical device makers, payers, and health systems where GPU compute bottlenecks, biological data pipeline complexity, or compliance requirements are barriers to accelerating AI development on CoreWeave.
- Build deep expertise across the HCLS AI stack (protein structure prediction and generative chemistry, molecular dynamics, genomics and multi-omics pipelines, medical imaging models, and clinical and operational LLMs), using CoreWeave's AI platform as the substrate that makes AI-native discovery and clinical AI economically viable.
- Translate customer requirements around PHI handling, HIPAA and GDPR compliance, GxP validation, data residency, and model governance into specific product feedback that shapes CoreWeave's roadmap for regulated industries.
- Develop deal structures, technical playbooks, and benchmark narratives that help sales and SA teams accelerate opportunities where training scale, pipeline throughput, and compliance posture are key evaluation criteria.
- Engage directly with heads of computational science, AI platform leads, CIOs, and research IT as the authoritative voice on GPU cluster architecture, secure AI infrastructure, and the compute decisions that separate research pilots from production-scale discovery and clinical programs.
- Design the commercial framework for large-scale HCLS infrastructure deals, including cluster reservation models, capacity commitments, and dataset storage SLAs, to support multi-year strategic partnerships.
- Partner with product, infrastructure, and ecosystem teams, including NVIDIA (BioNeMo, Clara, MONAI, Parabricks), scientific software ISVs, and data platform providers, to maintain a competitive edge across active and prospective HCLS deployments.
Who You Are:
- 10+ years of experience in technical business development, solutions architecture, or systems engineering within healthcare, life sciences, or AI infrastructure, with a track record of applying that expertise to drive customer outcomes and revenue.
- 5+ years working directly with pharma, biotech, or healthcare organizations on GPU infrastructure, scientific computing, or ML platform architecture in a customer-facing or deal-shaping capacity.
- Deep understanding of HCLS AI workloads: protein structure prediction, molecular dynamics and generative chemistry, genomics and multi-omics pipelines, medical imaging, and clinical NLP, and the infrastructure demands each creates.
- Working knowledge of the regulatory and privacy landscape governing healthcare and life sciences (HIPAA, GDPR, GxP and computer system validation, FDA expectations for AI/ML-enabled products) and how it shapes cloud adoption, vendor selection, and deal structure.
- Proven experience managing the full commercial lifecycle of complex technical deals exceeding $10M in contract value, including multi-stakeholder negotiation, technical due diligence, and deployment planning.
- Technical proficiency in cloud-native AI infrastructure including Kubernetes, high-speed storage systems (NVMe, object storage, parallel filesystems), and high-performance networking (InfiniBand, RDMA) as applied to large-scale training and scientific computing clusters.
- Demonstrated ability to build trusted relationships with senior computational science, engineering, and infrastructure decision-makers at pharma, biotech, and healthcare organizations.
The base salary range for this role is $177,000 to $237,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location.