Applied AI Engineer
A frontier-lab framing of forward-deployed work: an AI engineer pointed at a specific customer’s deployment.
An applied AI engineer builds retrieval pipelines, agents, tool schemas, guardrails and evals — the same toolbox as any AI engineer — but does it inside one customer’s environment and is measured on that customer’s outcome. Anthropic’s forward-deployed engineering sits under Applied AI, and the job description describes roughly 40% building, 30% customer-facing work and 30% carrying learnings back into the product.
Worked example: the deliverable for a quarter might be an MCP server plus a set of sub-agents handed to the customer’s team, with an eval suite that acts as the contractual acceptance test. Gotcha: the hard problem is usually organisational rather than technical — getting permission to touch the data and agreeing what “correct” means will consume more of the quarter than model work does.