

AI Engineering in Practice: Role, Skills, Industry Reality.
A practical guide to becoming a real-world AI engineer. Learn what end-to-end AI Engineering truly involves, how hiring works in today’s market, and how to build durable skills and experience - focusing on what actually works in real enterprises rather than chasing hyped technologies - to succeed in production environments.
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Fri Feb 20·4:00 PM UTC
What End-to-End AI Engineering Really Means
AI Engineering has become an overloaded term, shaped by rapidly evolving tooling, fragmented infrastructure and inconsistent role boundaries. As the discipline evolves, teams risk misalignment and fragile systems. Establishing a shared understanding of what End-to-End AI Engineering is, and what it is not, is essential for building AI systems that survive beyond demos and scale in production.
You'll learn from

Aurimas Griciūnas
Founder & CEO @ SwirlAI | Former CPO @ Neptune.ai (acquired by OpenAI)
Mon Feb 23·4:00 PM UTC
Getting Hired As AI Engineer in 2026
The AI engineering job market is rapidly changing, shaped by hype, automation, and an oversupply of similar-looking candidates. Without understanding how hiring actually works today, strong engineers are easily filtered out while weak signals dominate. Clarity on the current market, screening mechanics, and real hiring criteria is essential to compete and get hired in 2026.
You'll learn from

Aurimas Griciūnas
Founder & CEO @ SwirlAI | Former CPO @ Neptune.ai (acquired by OpenAI)

Danny Martinez
Co-founder @ Decimals
Wed Feb 25·4:00 PM UTC
Building Real AI Engineering Experience
Most AI engineers struggle to get hired not because they lack knowledge, but because they lack evidence of owning real systems. Hiring teams look for work that shows decisions, constraints, and failure handling. This topic matters because it explains how to build and present experience that can actually be evaluated and trusted.
You'll learn from

Aurimas Griciūnas
Founder & CEO @ SwirlAI | Former CPO @ Neptune.ai (acquired by OpenAI)