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LEARNING PATH · INTERMEDIATE

Backend Engineer → LLM Engineer

Build production LLM applications

Backend engineers have the systems thinking needed for LLM engineering. This path teaches prompt engineering, RAG systems, agent architectures, and deploying LLM apps to production.

4–8 months
8 hrs/week
2 tracks
$155,000–$230,000

TARGET ROLE

LLM Engineer, AI Backend Engineer

SALARY RANGE

$155,000–$230,000

DIFFICULTY

Intermediate

WHAT'S INCLUDED

Tracks in This Path

This path combines 2 curated learning tracks, sequenced to build on each other.

LEARNING OUTCOMES

What You'll Be Able To Do

By the end of this path, you'll have concrete, job-ready skills.

Master prompt engineering and few-shot learning

Build Retrieval-Augmented Generation (RAG) systems

Design and deploy AI agents with tool calling

Fine-tune LLMs for domain-specific tasks

Implement caching, error handling, and fallbacks for LLM calls

Ship a production LLM application to production

FAQ

Common Questions

Do I need to understand transformer internals?+
No. You're engineering systems with LLMs, not training them. Understand how to prompt, call APIs, and handle outputs reliably.
What's the hardest part of LLM engineering?+
Reliability. LLM outputs are non-deterministic. You'll learn techniques for grounding, validation, and fallback handling.
How quickly can I learn this?+
Fast. If you understand APIs and systems design, you can be productive with LLMs in 2–4 weeks. Mastery takes longer.

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Ready to start this path?

Take our 2-minute quiz to confirm this is the right path for you — or dive straight in.

Last updated: 2026-03-07