Applied AI Engineer, Enterprise

London · GBP 225,000-255,000 / year · 6+ years experience · Hybrid · Posted Sep 28, 2026

At a glance

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.

The Applied AI Engineer, Enterprise, acts as a technical advisor and Claude Platform specialist for large UK businesses.
This role involves guiding enterprise customers through technical evaluations, architecture design, and procurement to successfully deploy Claude into their operations.
The position requires balancing deep technical expertise in LLM applications with the ability to present business value cases to C-level executives.

Partner with Enterprise Account Executives and Applied AI Architects to manage the customer lifecycle from initial conversation to production deployment.
Lead the technical side of enterprise opportunities and serve as the ongoing technical advisor for Claude.
Define target architectures and advise systems integration partners on delivery standards.
Consult with customer engineering teams on architecture, agent design, and evaluation frameworks.
Present business value cases to C-level and senior executives, linking technical capabilities to measurable outcomes.
Navigate complex procurement processes, including security, compliance, data residency, and governance requirements.
Travel to customer sites across the UK as required.
Provide feedback from enterprise engagements to internal Product and Engineering teams.

6+ years of experience as a Software Engineer, Solutions Architect, Forward Deployed Engineer, or technical founder.
Pre-sales or technical advisory experience selling into large enterprises, ideally in the UK.
Experience owning the technical win, including evaluations, proofs of concept, and due diligence.
Experience with value-based selling and presenting business cases to C-level and VP-level stakeholders.
Production experience with LLM-powered applications, including prompting, context engineering, agent architectures, and evaluation frameworks.
Familiarity with enterprise security, compliance, and architecture requirements, ideally in regulated sectors.
Ability to explain complex AI concepts clearly to both technical and executive audiences.
Bachelor’s degree or an equivalent combination of education, training, and/or experience.

Location-based hybrid policy requires staff to be in the office at least 25% of the time.
Some roles may require more time in the office than the 25% minimum.