Manager Applied AI Architecture, Healthcare & Life Sciences

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.

As manager of the Healthcare and Life Sciences Solutions Architect team within Applied AI at Anthropic, you will drive the adoption of frontier AI in partnership with the rest of the go to market organization. We work with customers that include companies across payers, providers, life sciences, medtech, and other healthcare verticals. You will be responsible for leading and growing the pre-sales team that partners with account executives to help those companies understand and deploy Anthropic’s products, including Claude Code, Cowork, Claude Science, and the Claude Development Platform (our API). This will include leveraging your technical skills and consultative sales experience to hire great people, establish processes for the team to scale, and represent Anthropic directly at strategic customer engagements.

• Hire, manage, and guide a team of pre-sales Solutions Architects by providing both technical guidance and career development.
• Set goals for your team that establish baseline expectations for performance in collaboration with sales and other cross-functional teams.
• Act as a technical sponsor for high-value strategic customers and advise them on their overall AI adoption strategies or top use case scoping and deployment.
• Partner closely with sales leadership to identify new strategies to drive adoption of Anthropic products within specific verticals or horizontal use cases.
• Work with cross-functional teams like product and engineering to ensure Anthropic prioritizes customer feedback or resolves blockers to adoption.
• Travel to customer sites or conferences for executive-level sessions, technical workshops, and relationship building.
• Establish a shared vision for creating solutions that enable beneficial and safe AI in technology products.
• Contribute to thought leadership through conference presentations, webinars, and technical content creation.
• Stay current with emerging AI trends and the evolving ecosystem.

• 7+ years of experience as a Solutions Architect, Sales Engineer, or similar pre-sales technical role.
• 3+ years of technical pre-sales management experience.
• Have sold complex technical products to Healthcare and Life Sciences companies.
• Have deep technical proficiency with enterprise AI use cases and API integrations or enterprise solution rollouts.
• Understand how to contribute to running a GTM organization anchored on a consumption business model, not SaaS sales cycles.

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.

• Enterprise pre-sales leadership at scale: 5+ years leading solution architect teams through hypergrowth (ideally 10 to 50+ people), with direct experience managing senior individual contributors and developing junior talent in complex enterprise software sales environments.
• AI Technical Depth + Executive Engagement: Hands-on experience with AI platforms and enterprise integration patterns, combined with proven track record engaging C-level stakeholders in $10M+ technical evaluations and enterprise sales cycles.
• Deep HCLS GTM Experience: Demonstrated success adapting technical approaches to customers in payers, providers, life sciences, medtech, or other healthcare verticals.

$315,000—$380,000 USD

Logistics

Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience

Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience

Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.

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.