AI for Forward Deployed Engineers
Aishwarya Srinivasan
AI Entrepreneur | Ex-Google, Microsoft
Arvind Narayanamurthy
AI Engineering Lead | Founder
Master the FDE skills companies now expect
Forward Deployed Engineering is becoming one of the most important roles in AI because companies are no longer just asking, “Can we build a demo?” They are asking, “Can this agent work inside our real customer environment?”
That requires a very different skill set. FDEs need to understand how LLMs behave, how RAG systems fail, how agents call tools, how enterprise APIs and knowledge bases fit together, and how to deploy systems that can handle latency, cost, scale, security, and reliability constraints.
This workshop is designed to bridge that exact gap. You will go from AI fundamentals to building a working agent, connecting it to real tools and enterprise systems, and deploying it on Google Cloud with Vertex AI. The goal is not surface-level AI literacy. The goal is to think, build, debug, and ship like the engineer companies trust to take AI from prototype to production.
What you’ll learn
You’ll learn to build, debug, deploy, and explain production AI agents like a Forward Deployed Engineer.
Develop agents with LLM APIs, tools, knowledge bases, and enterprise systems.
Understand agent loops, tool calling, structured outputs, and guardrails.
Build a working LangGraph agent that answers from real APIs and internal data.
Reason through tokens, context, embeddings, RAG, and failure modes.
Debug hallucinations, retrieval failures, bad tool calls, and brittle workflows.
Evaluate agents using observability, evals, HITL, and production-grade checkpoints.
Move from local prototype to hosted endpoint on Google Cloud and Vertex AI.
Understand deployment paths, Model Garden, scaling, and cloud operations.
Make trade-offs across latency, cost, reliability, security, and customer impact.
Workshop agenda
Module 1: AI Building Blocks
AI foundations for FDEs: how LLMs work, embeddings, RAG, failure modes, agent patterns, tool calling, schemas, and structured outputs.
Module 2: End-to-End Agent Development
End-to-end agent build: use LangGraph, real tools, knowledge bases, LLM APIs, evals, observability, guardrails, and HITL.
Module 3: Deploying Agents on GCP
Cloud deployment for AI agents: Vertex AI, Model Garden, GCP hosting, production operations, latency, cost, and scaling trade-offs.
Learn directly from Aishwarya & Arvind
Aishwarya Srinivasan
AI Entrepreneur | Ex-Google, Microsoft
Arvind Narayanamurthy
AI Engineering Lead | Founder
Who this workshop is for
Future FDEs
For people who want to break into Forward Deployed Engineering or AI implementation roles.Customer-facing technologists
For solutions engineers, TAMs, consultants, and architects moving closer to AI systems.AI career switchers
For engineers and technical professionals transitioning into agentic AI and production AI roles.
What's included
Live sessions
Learn directly from Aishwarya Srinivasan & Arvind Narayanamurthy in a real-time, interactive format.
Lifetime access
Go back to course content and recordings whenever you need to.
Community of peers
Stay accountable and share insights with like-minded professionals.
Certificate of completion
Share your new skills with your employer or on LinkedIn.
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Frequently asked questions
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Reimbursement
Get your company to pay
Everything L&D needs: email template, receipts, and certificate of completion.
Get reimbursedTeam discount
Learn with your teammates
Save 20%+ when 2 or more teammates enroll in the same cohort.
Save 20%+ with a teamPrivate cohort
Run a cohort for your org
A dedicated cohort with a custom schedule and curriculum, tailored to your team.
Book a private cohort$599
USD
11am–2:30pm EDT