Switching to AI Roles: What Engineers Need to Learn, Build & Show
Note: This is an online event. Meeting link will be shared closer to the event.
About Event:
A large number of engineers today are trying to move into AI.
They’re taking online courses, building small projects, and experimenting with tools, yet very few actually break into serious AI roles.
The problem usually isn’t effort.
It’s a lack of clarity around what skills actually matter, what projects get noticed, and how to position yourself when making the transition.
In this session, Divij Bajaj shares a practical and honest perspective on what it really takes to move from traditional software roles into Applied AI and Data Science.
Drawing from his own transition into AI systems work at Microsoft, the conversation will focus on the real decisions engineers need to make - the foundations to build, the projects that signal real capability, and how to avoid getting stuck in the endless learning loop.
If you’re a developer exploring AI, this session will help you separate hype from reality and design a clearer path forward.
What We’ll Cover:
Why learning AI online often doesn’t translate into AI jobs
The technical foundations that matter most
What kinds of AI projects get noticed by recruiters
How engineers should position themselves for AI roles
The common mistakes engineers make when transitioning
A practical roadmap into Data Science and Applied AI
Who This Is For:
Software engineers and backend developers exploring a move into AI or ML
Tech professionals who have started learning AI but feel stuck
Developers evaluating structured pathways into Data Science or Applied AI
Engineers who want to understand how AI hiring actually works
#AI #CareersInAI #SoftwareDevelopers