u/WaveSuch7542

I’m currently learning LangChain, LangGraph, FastAPI, and PostgreSQL, and I’ve already built a few projects using these technologies.

I’m planning to graduate in May 2027, and I’m trying to decide what I should focus on next to become more industry-ready.

Would it be a good idea to add React.js to my current stack and aim for a Full-Stack AI Engineer profile?

My thinking is:

Python + FastAPI + PostgreSQL + LangChain + LangGraph + React

For those already working in AI engineering, backend, or full-stack AI roles:

Is Full-Stack AI Engineering a good career path for the next few years?

Would learning React significantly improve my opportunities, or should I go deeper into AI/ML instead?

What skills are companies currently looking for in AI engineers?

What would you recommend I learn or build before graduating in 2027?

Are there good opportunities for this profile in Pakistan or internationally?

I’d really appreciate advice from people already working in the industry or hiring for these kinds of roles.

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Hi Salam everyone,

I'm a senior-year AI undergraduate currently looking for a remote internship where I can contribute, learn, and gain real-world experience in AI.

My areas of expertise include:

* Machine Learning

* Deep Learning

* LangChain

* LangGraph

* LangSmith

* Retrieval-Augmented Generation (RAG)

* Agentic AI

* LLM Fine-tuning

* FastApi

I've built AI applications involving RAG pipelines, multi-agent systems, tool calling, MCP, and production-ready ML workflows. I'm passionate about solving real-world problems and continuously improving my skills.

If your company is hiring interns, or if you know of any remote AI/ML internship opportunities, I'd be grateful if you could point me in the right direction.

Thank you for your time!

I’m using Llama 3 3B Instruct (free tier) for structured outputs with Pydantic schemas, but it’s pretty inconsistent.

Issues I’m facing:

Missing tool calls

Weak tool calling reliability

Needs lots of retries and fixes

Looking for suggestions on models that handle structured output better (free or open-source).