You'll leverage your technical skills and consultative sales experience to drive positive AI transformation that addresses our customers' business needs, meets their technical requirements, and provides a high degree of reliability and safety.

Responsibilities:

• Hire, manage and mentor a team of Applied AI Architects for Northern Europe, providing both technical guidance and career development
• Set goals and reviews for your team, promoting growth and output
• Work with a handful of highest-value enterprise customers on their overall AI adoption strategies, focusing on pre-sales technical excellence including use case scoping, architecture reviews, technical champion building, technical adoption workshops and POC execution
• Partner closely with your aligned GTM leadership to understand customer requirements and co-build GTM strategies to drive adoption across all industry verticals
• Own the technical portions of pre-sales engagements, ensuring your team provides compelling demos and validates customer ROI from Anthropic products
• Develop scalable technical engagement frameworks and reusable assets tailored for all non-tech sectors, including Financial Services & Insurance, Healthcare, Telco, Retail and others.

You may be a good fit if you have:

• 7+ years of experience as a Solutions Architect, Sales Engineer, or similar pre-sales technical role
• 3+ years of technical go-to-market management experience, specifically managing pre-sales teams
• Experience working with and selling to large enterprise customers across multiple verticals
• Demonstrated ability to navigate and articulate complex technical, organisational and regulatory requirements of large enterprises, in particular in regulated industries (e.g FSI, Healthcare & Life Sciences)
• A proven knowledge of the Northern European market and its local specificities (regulatory, cultural, technical…)
• Experience framing and delivering enterprise AI use cases (productivity, workflow transformation) and/or scoping large enterprise adoption programs
• Deep technical proficiency with enterprise AI deployments, API integrations, and production LLM use cases
• Demonstrated ability to build scalable, repeatable processes and frameworks that work across diverse customer segments
• An organisational mindset and enjoy building foundational teams in a relatively unstructured environment
• Excellent communication, collaboration, and coaching abilities
• Comfort dealing with highly uncertain, ambiguous, and fast-moving environments
• Strong executive presence and ability to foster deep relationships with technical leaders and engineering teams
• High-level familiarity with the architecture and operation of LLM and/or ML in general
• Experience with prompt engineering, LLM evaluation, and architecting AI-powered systems
• Ability to make ambiguous problems clear and identify core principles that can translate across scenarios
• A passion for making powerful technology safe and societally beneficial
• Creative thinking about the risks and benefits of new technologies, beyond past checklists and playbooks
• A track record of staying current with emerging AI research and industry trends or similar.

Strong candidates may also have:

• 10+ years technical experience
• 5+ years managing AI technical teams in hypergrowth (ideally from 10 to 50+)
• Previous experience leading solutions architect or pre-sales teams through rapid growth
• Proven experience and understanding across all key non-tech industry verticals, in particular the regulated industries: Financial Services, Insurance, Healthcare, Life Sciences, Telco, Retail, Consumer Goods, Manufacturing, Oil & Gas, etc.
• In addition to English, native or fluency in a Northern European language
• Demonstrated experience in defining and delivering enterprise AI use cases in regulated industries: e.g, Banking, Insurance, Healthcare and Life sciences
• Track record of building technical playbooks and assets that scale across diverse customer segments
• Understanding of both digital-native technical requirements (API integration, developer experience) and traditional enterprise needs (security, compliance, change management)
• Background at enterprise AI software or API-first companies serving large enterprise customers
• Proven experience building a Northern European AI team

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