FDE Instructor

What you will do
Host live events focused on deploying AI systems inside a client's environment: discovery and scoping, agentic architecture, integration with enterprise systems, rollout, and adoption
Run 1:1 sessions and tech mock interviews for students working through projects
Review student projects against rubrics, including the client-facing side of the work: scoping decisions, demos, and how they explain a system to a non-technical stakeholder
Set the technical standard for a team of supporting instructors who cover questions and first-line review, and act as their escalation point

Requirements
7+ years of professional engineering experience, currently working at senior level or above (Senior/Lead/Staff Engineer, Forward Deployed Engineer, Solutions Architect, or technical lead on customer-facing delivery)
Has personally owned deployments end to end in real client or enterprise environments – first call through production go-live and adoption
Depth across the FDE spine: customer discovery and design sessions, scoping and delivery planning under ambiguity, stakeholder management without formal authority; LLM and agent systems in production (prompting, tool/function calling, orchestration frameworks such as LangGraph/LangChain/CrewAI, guardrails, evals, RAG over enterprise data); APIs and integrations (REST, webhooks, JSON/GraphQL), Python, and deployment on at least one major cloud
Can explain why an architecture or scoping decision was made, not just how it was implemented, and can diagnose and critique someone else's work live
Strong technical communication: translating between technical and business audiences, comfortable leading a live session, whiteboarding a solution, and writing clear, specific review feedback
Strong English C1+ — instruction and review are in English for a US-based audience
Comfortable using AI tools in day-to-day technical work

Preferred experience:

Has taught, mentored, or run technical sessions before: internal tech talks, onboarding, mentoring engineers, bootcamp or workshop instruction
Has worked embedded with a customer team as their primary technical resource, or held a customer-facing engineering role (solutions engineer, solutions architect, technical consultant)
Production experience with agentic frameworks (LangGraph, LangChain, CrewAI) and MCP-based tool integrations into client systems
Work experience at a recognizable company
Familiarity with online education platforms or running programs