Applied AI Engineer, DNB en Anthropic

Híbrido - London, UK

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Applied AI Engineer on the Digital Native Business team helps fast‑growing, tech‑forward companies build products on Claude. The role involves serving as a technical advisor, working closely with customer engineering teams on pair programming, architecture reviews, and code contributions, developing prototypes and technical documentation, creating technical content for developers, fostering community engagement through events, and traveling to customer sites for workshops and support.

Salary

GBP 225,000 - 255,000

Requirements

Skills

  • 4+ years experience as a Software Engineer, Forward Deployed Engineer, or technical founder
  • Experience in a customer-facing or pre-sales technical role partnering with customers
  • Production experience building LLM-powered applications, including prompting, context engineering, agent architectures, evaluation frameworks, and deployment at scale
  • Strong programming skills with proficiency in Python
  • Experience working with high-growth, tech-forward companies
  • Ability to context-switch across industries and use cases
  • Builder credibility with a track record of shipping products
  • Strong technical communication skills to translate complex AI concepts into actionable plans
  • Experience facilitating technical workshops, hackathons, or developer-focused events
  • Passion for making powerful technology safe and beneficial
  • Minimum education: Bachelor’s degree or equivalent

Responsibilities

  • Serve as a deep technical advisor to high-growth, tech-forward companies, working alongside them to build innovative use cases that push the boundaries of AI
  • Work hands-on with customer engineering teams: pair programming, architecture reviews, and code contributions
  • Develop prototypes and technical documentation—including evaluation suites, AI engineering techniques, and architecture diagrams—that enable customers to build and scale with Claude
  • Collaborate closely with Applied AI Architects to maintain context and continuity across customer engagements
  • Identify patterns across engagements and contribute insights back to Product, Engineering, and the broader Applied AI team
  • Create technical content for developer audiences including documentation, tutorials, and sample code
  • Foster community engagement through hackathons, webinars, technical office hours, and developer-focused events
  • Travel to customer sites for workshops, implementation support, and relationship building

Technologies

PythonLarge Language Models (LLM)Claude (Anthropic’s model)PromptingContext engineeringAgent architecturesEvaluation frameworksDeployment at scale

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