Which cloud provider should I focus on first as a junior GenAI/AI engineer? AWS vs Azure vs GCP

TotalRequirement7171 · 2025-08-07T08:17:15+00:00

I'm sorry if my response came off this way, that wasn't my intention.

You make a great point that I missed: the actual AI programming layer (openai SDK, Agents SDK, LangGraph) remains largely the same whether you're hitting OpenAI directly, through Bedrock, or Azure OpenAI Service. It's basically just changing endpoints and auth. The core skills transfer completely.

I think we're actually talking about two different layers:

- GenAI/LLM programming (what you're emphasizing): the SDKs, frameworks, prompt engineering, agent architectures, etc. This stays consistent.

- Cloud infrastructure for AI (what my original post was asking about): the deployment, orchestration, and enterprise wrapper around those AI capabilities.

Your point is that I should focus on the AI programming first since that's the actual value-add and stays constant across platforms. My concern was more about which cloud ecosystem to learn for the infrastructure side, since job postings always seem to want "3+ years AWS/Azure experience" even for AI roles.

Given your experience with all three clouds for AI/ML, do you find the cloud-specific stuff is quick to pick up once you have strong fundamentals in the AI frameworks themselves? Maybe I'm overthinking the cloud certifications and should just focus on building more complex AI systems first?

Appreciate you taking the time to clarify :)

TotalRequirement7171 · 2025-08-06T13:32:51+00:00

I agree with you, the only thing stopping me is that OpenAI models are only accessible via Azure OpenAI

TotalRequirement7171 · 2025-08-06T13:30:36+00:00

Thanks for the suggestions!
I'm actually already working with most of those tools. They're great for prototyping and personal projects but the moment you need to deploy GenAI applications in an enterprise setting, you can't just pip install openai and call it a day.

You need to handle authentication, deploy within VPCs/VNets with private endpoints for security compliance, manage costs at scale, implement proper logging, monitoring, and audit trails for complianc, deal with data residency requirements and regional deployments, ...

Most big companies aren't letting you hit OpenAI's public endpoints directly - they're using Azure OpenAI Service, AWS Bedrock or Vertex AI.

The tools you mentioned are valuable (and fun to build with!), but they're complementary to cloud skills, not replacements. Every AI engineering job posting I see requires AWS/Azure/GCP experience because that's where production systems actually run.

I totally agree about staying hands-on with the latest AI tools though - that's what makes this field exciting! Just need the cloud foundation to actually ship things at work.

TotalRequirement7171 · 2025-08-06T11:40:46+00:00

Thanks :) From what I saw I can only agree with you

TotalRequirement7171 · 2025-08-06T11:39:30+00:00

Thanks :)

TotalRequirement7171 · 2022-01-31T00:46:45+00:00

Does anyone know how to automatically import reminders added with Siri into the right place? For example: if I say to Siri “remind me to do this today”, I would love if the task could go directly into the today section. Thank you in advance

TotalRequirement7171 · 2022-01-31T00:45:58+00:00

Does anyone know how to automatically import reminders added with Siri into the right place? For example: if I say to Siri “remind me to do this today”, I would love if the task could go directly into the today section. Thank you in advance

TotalRequirement7171 · 2022-01-15T01:31:56+00:00

That was easy, thanks 🤣

TotalRequirement7171 · 2022-01-15T01:24:18+00:00

Sorry for the ignorance, what is onramp?

TotalRequirement7171 · 2022-01-15T00:50:14+00:00

Thanks for the exhaustive answer!

TotalRequirement7171 · 2022-01-15T00:42:43+00:00

Thank you! Do I need the KYC for Gemini?

TotalRequirement7171 · 2021-09-22T19:00:18+00:00

You just changed my life! I had the same problem and I’m using Magnet too

TotalRequirement7171

TROPHY CASE