Applied AI Engineer, Enterprise

Overview In this role you guide UK enterprise customers to adopt Claude, acting as a platform specialist and trusted advisor. You translate technical capabilities into business value, leading architecture and evaluation discussions with engineering teams and C-level sponsors.

You drive multi-quarter engagements from first conversation to production deployment, aligning security, compliance, and governance with customer needs. You collaborate with product, engineering, and enterprise teams to scale Claude deployments and accelerate customer outcomes.

Pay / Benefits visa sponsorship flexible working hours generous vacation and parental leave equity donation matching (optional) collaborative office space Responsibilities Partner with Enterprise Account Executives and Applied AI Architects to move customers from initial contact through procurement to build-on-Claude decisions Lead the technical aspects of opportunities and remain the customer's Claude advisor during deployment Define target architecture, establish success criteria, and guide delivery teams during build Help customer engineers design Claude-based architectures, agent designs, and evaluation frameworks Build and present a business value case for Claude to C-level and VP stakeholders, tying capabilities to measurable outcomes Navigate multi-stakeholder procurement processes including security, architecture reviews, data residency and governance (UK GDPR) Feed enterprise-experience patterns back to Product/Engineering and travel to customer sites in the UK Key requirements 6+ years in Software Engineer, Solutions Architect, Forward Deployed Engineer, or technical founder roles Pre-sales or technical advisory experience selling to large enterprises in the UK Experience with value-based selling and presenting business cases to executives Production experience with LLM-powered applications: prompting, context engineering, agent architectures, evaluation, and scalable deployment Familiarity with enterprise security, compliance, and architecture requirements, ideally in regulated sectors Ability to explain complex AI concepts to technical and executive audiences, with a passion for safe and beneficial AI strong communication and storytelling for executive audiences stakeholder management across multi-quarter engagements collaboration with cross-functional teams LLM-powered application development prompting and context engineering agent architectures and evaluation frameworks

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