Career Tracks
Two years ago, a job title like “Prompt Engineer” didn't exist. Today, companies are inventing new roles just to describe what AI lets one person do — deploy a working agent for a customer in an afternoon, keep a fleet of AI agents reliable in production, or sell an enterprise on an AI rollout that used to take a whole team to explain.
Most of these roles are variations on jobs that already exist — software engineer, product manager, reliability engineer, sales engineer — reshaped by what AI now makes possible. The core skills transfer; what's new is the AI-specific layer on top.
Pick a role below to see what it actually involves: what you'd do day to day, what to learn first, how to prepare for the interview, and how much of this curriculum you need before you're ready to apply.
Forward-Deployed Engineer (FDE)
Embedded with a customer, shipping production AI inside their org. The deepest track: full curriculum plus judgment skills the labs alone don’t teach.
Live nowApplied / Agentic AI Engineer
The core hands-on builder role: RAG systems, tool-using agents, and multi-agent orchestration.
Live nowAI Product Manager
Decides what gets built, not how it’s built. A non-coding, decision-making track — approachable even with zero prior technical background.
Live nowSRE / Reliability Engineer for AI Agent Applications
Keeps AI agents running reliably in production: observability, guardrails, and cost/latency budgets.
Live nowAI Solutions Architect / Presales Engineer
Pre-sales and consulting: demoing, proposal-writing, and requirement analysis for enterprise AI adoption.