Forward Deployed AI Engineer-Anthropic-UK

A senior forward deployed AI engineer is needed to translate enterprise business problems into secure, production-grade AI solutions built on a leading large language model platform. The role blends full-stack engineering, LLM application design, and client-facing delivery, with roughly a quarter of the time spent traveling to customer sites. It sits at the intersection of consulting, enterprise integration, and applied generative AI.

• Deploy, configure, and operationalize agentic AI workflows, assistants, and automations inside customer enterprise environments
• Translate business requirements and operational processes into technical architectures and production-ready AI solutions
• Apply prompt and context engineering, structured outputs, tool use, function calling, and human-in-the-loop review patterns
• Build retrieval-augmented generation systems grounded in authorized enterprise data and knowledge sources
• Improve reliability through citation patterns, validation, confidence thresholds, output schemas, and escalation workflows
• Run workshops, discovery sessions, technical demonstrations, pilots, and production rollouts
• Communicate AI capabilities, limitations, and tradeoffs to both technical and business stakeholders
• Contribute reusable components, prompt assets, and improvements back into internal AI platforms and accelerators

• 5-8 years in software engineering, systems integration, enterprise platforms, or workflow automation
• Hands-on experience with full-stack development, APIs, microservices, enterprise integrations, or cloud-native applications
• Experience building LLM-powered applications, RAG systems, AI assistants, or agentic workflows
• Proficiency in JavaScript or Type Script, Python, or comparable programming languages
• Familiarity with AWS, Microsoft Azure, or Google Cloud
• Working knowledge of prompt engineering, embeddings, vector search, structured outputs, and model evaluation
• Understanding of responsible AI concepts, including hallucination mitigation, sensitive data handling, access controls, and human oversight
• Track record operating in customer-facing engineering, consulting, or technical implementation roles

• Hands-on experience with a major enterprise workflow platform, including integration tools, virtual agents, AI agents, and platform development patterns
• Familiarity with enterprise data models such as CMDB, ITSM, CSM, HRSD, knowledge management, and workflow tables
• Experience with vector databases, document ingestion, chunking, and retrieval strategies
• Use of orchestration frameworks such as Lang Chain, Lang Graph, Llama Index, or Semantic Kernel
• Exposure to AI observability, tracing, evaluation frameworks, and prompt or version management
• Comfort with Docker, CI/CD, SQL, Git, infrastructure-as-code, and secure cloud deployment