Senior/Lead Forward Deployed AI Engineer-Anthropic-US West

Role overview

A senior Forward Deployed AI Engineer is needed to design, build, and operationalize generative AI workflow solutions directly inside enterprise customer environments. The role sits at the intersection of full-stack engineering, LLM implementation, enterprise integration, and customer-facing delivery, translating real business problems into secure, reliable, production-grade AI systems. The position is remote with approximately 70% travel to client sites.

Responsibilities

- Deploy, configure, and operationalize agentic AI workflows, AI assistants, and automations inside customer enterprise platforms and surrounding technology ecosystems. - Translate business requirements, operational processes, and desired outcomes into technical architectures, implementation plans, and production-ready AI solutions. - Build enterprise AI applications using leading large language model APIs, applying prompt and context engineering, retrieval-augmented generation, tool use, structured outputs, multi-step orchestration, and human-in-the-loop review patterns. - Develop prototypes, demos, and proofs of concept that validate AI-driven workflows, then iterate based on feedback, performance, and operational signals. - Communicate AI capabilities, limitations, and tradeoffs to both technical teams and business stakeholders during discovery, workshops, pilots, and production rollouts. - Contribute reusable components, prompt assets, accelerators, and customer-driven feedback that improve internal AI platforms and shared delivery patterns.

Requirements

- 8+ years of experience in software engineering, systems integration, enterprise platforms, workflow automation, or related technical delivery roles. - Strong hands-on foundation in full-stack development, scripting, APIs, microservices, enterprise integrations, or cloud-native applications. - Experience building or supporting AI or LLM-powered applications, RAG systems, conversational experiences, or agentic workflows in production environments. - Proficiency in JavaScript or TypeScript, Python, or comparable programming languages. - Hands-on experience with at least one major cloud platform such as AWS, Microsoft Azure, or Google Cloud. - Working knowledge of responsible AI concepts, including hallucination mitigation, sensitive-data handling, identity controls, human oversight, and secure deployment.

Nice to have

- Familiarity with major enterprise service management platforms and their data models, including CMDB, ITSM, CSM, HRSD, knowledge management, and workflow integrations. - Experience with vector databases, embeddings, document ingestion, chunking, retrieval strategies, and knowledge-grounding patterns. - Exposure to LLM orchestration frameworks such as LangChain, LangGraph, LlamaIndex, or Semantic Kernel. - Comfort with AI observability, tracing, evaluation frameworks, prompt and version management, and cost optimization. - Familiarity with Docker, CI/CD, SQL, Git, infrastructure-as-code, and secure cloud deployment practices.

Benefits and work setup

- Remote role with approximately 70% travel to customer sites. - Inclusive, equal-opportunity workplace with accommodations available for candidates with disabilities.