The demo went well. Six weeks later nothing is in production, the customer has gone quiet, and nobody can say exactly what went wrong. Closing that gap is the job. A forward deployed engineer embeds with an enterprise customer, works out what the real problem is, builds inside their environment and their constraints, and stays until the thing is running and used. Part engineer, part product manager, part consultant. The role pays what it does because very few people are all three at once, in front of a customer, under time pressure.
This course teaches that work end to end. It is built around one project rather than a playlist of topics. In Section 3 you pick a messy document set you did not create — a mailbox export, a folder of scanned PDFs, a filings archive. You frame the problem, prototype against it, build an eval set, instrument it, take it through a security review, deploy it behind a private endpoint and hand it over with a runbook. Nothing restarts. By Section 11 you hold the two artifacts hiring managers actually screen for: a system that runs with monitoring and measurable quality, and a written brief an executive would read.
The technical half is current. Workflows against agents and the five composable patterns. Retrieval over data with real permissions attached, not a tutorial corpus. Evaluation as a discipline — offline and online, LLM-as-judge and where it lies to you, trajectory against outcome for agents. OpenTelemetry tracing with GenAI span conventions. SLOs and error budgets. Prompt injection, excessive agency, and the OWASP and NIST vocabulary a customer’s security team will use on you. Containers, rolling updates, and the private-networking patterns that decide whether a deployment is allowed to exist.
