AI Engineering Fundamentals
2-3 weeksSkills You'll Build
Python for AI if not already proficientLLM landscape and capabilitiesAI engineering vs traditional developmentKey AI tools and frameworksIndustry terminology and trends
Software Contractor/Freelancer → Full-Time AI Engineer
Contractor to AI Employee: From Gig Work to Stable AI Engineering Roles
You've been contracting, maybe loving the flexibility, maybe tired of the hustle. Either way, you want to transition into a stable full-time AI engineering role with benefits, career growth, and interesting problems. This path isn't about learning from scratch; it's about positioning your existing skills for AI roles and filling specific gaps that interviewers look for. Your contracting experience means you've seen many codebases, adapted quickly, and delivered under pressure. Now let's package that into a compelling AI engineering candidacy.
2-4 months
Prerequisites
- Professional software development experience
- Experience with multiple tech stacks
- Self-directed learning ability
- Track record of delivered projects
- Basic understanding of APIs and databases
Your Learning Path
LLM APIs and Implementation
3-4 weeksSkills You'll Build
OpenAI and Claude API masteryPrompt engineering patternsFunction calling and tool useStreaming and async patternsError handling and resilience
RAG and Vector Systems
3-4 weeksSkills You'll Build
Embedding models and similarityVector database selectionBuilding production RAG pipelinesEvaluation and optimizationHybrid search strategies
AI System Architecture
2-3 weeksSkills You'll Build
FastAPI for AI servicesDatabase patterns for AICaching and performanceMonitoring and observabilitySecurity considerations
Interview Prep and Portfolio
2-3 weeksSkills You'll Build
AI engineering interview patternsSystem design for AI questionsPortfolio projects that impressConverting contracts to referencesSalary negotiation for full-time