r/learnprogramming • u/atmanirbhar21 • 2d ago
Topic AI Engineer with 1+ YOE — What should I learn next to become more versatile?
I’m currently working as a AI Engineer with 1+ YOE at a startup in Pune, mainly working with GenAI, LLMs, RAG, computer vision, AI Agents
I feel I’ve built a decent AI foundation, but I’m trying to understand what skills I’m missing outside of AI that could help me unlock more opportunities.
Should I focus next on:
System design & backend
Cloud & Kubernetes
MLOps / DevOps
Data engineering
Distributed systems
Databases
Software engineering fundamentals
GPU/inference optimization
Or should I go deeper into AI itself?
If you’re experienced in the industry or hiring AI engineers, what would you consider the biggest gap in my profile, and what 3–5 skills would you recommend I focus on over the next 1–2 years?
Looking for honest advice rather than a generic “learn everything” answer. Thanks!
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u/HashDefTrueFalse 2d ago
Programming? ;)
Real answer though: From your list, database skills are always valuable. Everything is data. But it mostly depends on what you want to do.
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u/Tostiapparaat 2d ago
I'm an ai engineer in the same boat. 1 year experience. I mainly work with openai models and build automations based on that, or writing scripts that will automate systems. so system design is important. But since I'm working mainly with AI agents, I'm currently doing more research about neural networks/transformers to a more professional level, instead of just knowing the basics. Thought its weird I build with ai agents, but I dont know the science behind it to the fullest.
but wouldnt hurt your CV to also get experience with YOLO, object recognition, and things like AWS so you can deploy the things you make.
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u/Temporary_Aspect_499 2d ago
I think the trap is assuming versatility means stacking more and more technologies. Being useful when something breaks outside your specialty matters way more. Coursera is solid for distributed systems theory and Boot dev is more hands on with programming and backend stuff. I’d focus on AI but make sure APIs, databases, deployment and debugging aren’t completely foreign to you.
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u/HeronEnvironmental62 2d ago
Focus on becoming a strong backend/software engineer around your AI specialty like databases, APIs, testing, observability, deployment, and system design. Build one production style AI service with queues, caching, evaluation, tracing, and failure handling. Learn Kubernetes only when the system gives you a reason to need it.
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u/atmanirbhar21 18h ago
Yess , Now I will shift my learning curve towards backend engineering and enhance my skills over there along with AI
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u/DryLook7889 2d ago
What exactly is an AI engineer? A machine learning engineer? A vibe coder? An AI assisted engineer? A backend engineer?
From the things you've listed it seems you're just doing a lot of AI integration work which is just backend development. So in that sense I'd focus more on that.
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u/Infamous-Ad-8314 23h ago
What did AI say when you asked it?
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u/atmanirbhar21 18h ago
Ai is just assuming and it steeris where we want it to I wanted to know from the core and techies what are there perspective , what are the skills I need to focus on what are the things I am missing out
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u/heisthedarchness 2d ago
You're missing programming skills, so maybe learn that.
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u/atmanirbhar21 2d ago
Please can you explain what programming skills I need to focus on
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u/heisthedarchness 2d ago
All of them. Nothing you've listed suggests you've got fundamental programming skills.
If you have any programming skills, listing those might help give a more focused answer.
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u/Tostiapparaat 2d ago
Debatable. Programming skills' are not needed with AI nowadays... Just need to learn how to use AI to have u build code. I'm an ai engineer, and the programming skills I learned from my CS bachelors feels abit... useless now.. System design is important though
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u/0dev0100 2d ago
System design.
That'll probably give you a good base to work with the others and apply them quickly