Enterprise Account Executive, Healthcare & Life Sciences
London, UKFull-TimeMid-levelAccounts / Finance
About Anthropic
- Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About the role
- We're seeking an experienced Enterprise Account Executive to drive adoption of Anthropic's AI solutions across healthcare payors and providers throughout the EMEA markets. In this role, you'll leverage your deep understanding of the healthcare ecosystem to help organizations transform patient care, optimize operations, and improve outcomes through responsible AI implementation.
Responsibilities
- Develop and execute strategic sales plans to drive adoption of Anthropic's AI solutions within payor and provider organizations
- Build and maintain relationships with key decision-makers in major healthcare systems, health plans, and integrated delivery networks
- Partner with our HCLS Applied AI team to articulate technical capabilities and develop compelling value propositions for healthcare-specific applications
- Identify and qualify new opportunities through discovery calls, demonstrations, and collaborative problem-solving sessions
- Navigate complex buying processes, negotiate contracts, and close enterprise deals
- Leverage our strategic partnerships (including AWS) to expand our reach in the healthcare market
- Monitor and report on sales pipeline, market trends, and competitive landscape
- Capture and communicate industry-specific requirements to inform product development
- Represent Anthropic at healthcare industry events and conferences
- Collaborate cross-functionally to ensure our solutions address healthcare-specific challenges around data privacy, security, and regulatory compliance
You may be a good fit if you have
- 8+ years of enterprise sales experience within the UK/EMEA market, with at least 5 years selling technology solutions to healthcare payors and providers
- Proven track record of exceeding quota and closing complex enterprise deals in the healthcare sector
- Deep understanding of healthcare industry dynamics, including revenue cycle management, value-based care models, population health, and digital transformation initiatives
- Experience navigating lengthy procurement cycles and multi-stakeholder decision processes
- Strong relationships with senior executives in payor and provider organizations
- Ability to translate technical capabilities into business value and ROI
- Experience collaborating with technical teams to develop tailored solutions
- Excellent communication and presentation skills
- Knowledge of healthcare data privacy regulations (GDPR, etc.) and security requirements
- The annual compensation range for this role is listed below.
- For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
How we're different
- We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
- The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
