GTM Solution Specialist - Healthcare & Life Sciences

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:

AI is transforming how medicines are discovered, how diseases are diagnosed, and how care is delivered. Pharmaceutical companies, biotechs, medical device makers, payers, and health systems are moving AI from research into regulated production: training foundation models on genomic, molecular, and imaging data, running large-scale protein structure prediction and molecular dynamics, and deploying clinical and operational LLMs under strict privacy and validation requirements. Building these systems demands extraordinary compute, and it demands infrastructure that can meet the compliance bar of a regulated industry. 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. You feed what you learn directly into the product roadmap, and you equip the broader sales and solution architecture teams with the domain knowledge and deal frameworks to win in HCLS.

About the role: As a GTM Solution Specialist for Healthcare & Life Sciences, you sit at the front edge of CoreWeave's go-to-market motion for an industry where AI is compressing decade-long discovery timelines into years. This is a market-creation role: you take CoreWeave's AI platform into accounts where foundation model training, genomics pipelines, and clinical AI deployment are becoming infrastructure-defining decisions, win the first HCLS customers, and build the repeatable narratives and playbooks the rest of the field uses to scale. You are the connective tissue between computational science and clinical AI teams and CoreWeave's product and infrastructure roadmap, translating what early customers need around petabyte-scale biological data pipelines, regulated workload isolation, and validated environments into the priorities that make CoreWeave the essential AI cloud for healthcare and life sciences.

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.

Preferred:

Direct experience at or selling into leading HCLS organizations (global pharma, techbio and AI-first drug discovery companies, genomics platforms, medical imaging or device leaders, or major health systems and payers).

Familiarity with NVIDIA's healthcare and life sciences ecosystem, including BioNeMo for biomolecular foundation models, Parabricks for genomics, and MONAI and Clara for medical imaging, at both a technical and commercial level.

Background supporting large-scale scientific computing, structure-based drug discovery pipelines, or clinical AI deployment in a validated environment.

Advanced technical degree (MS or PhD in Computational Biology, Bioinformatics, Computer Science, or equivalent) or MBA with a strong technical foundation in AI/ML systems, and a demonstrated ability to operate at the intersection of technical architecture and commercial strategy.

Wondering if you're a good fit?

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 understand the HCLS AI stack end-to-end: you know how sequencing reads and molecular structures become training tensors, how foundation models compress years of wet-lab iteration into weeks of compute, and how to explain both to a Chief Scientific Officer and a CFO in the same meeting.

You are fluent in where the industry is heading: you follow how biomolecular foundation models, AI-native drug discovery, and clinical L