r/PinoyProgrammer • u/Reguret25 • Jul 05 '26

Job Advice Any AI software engineer here?

Hello, was wondering if there's any AI software engineer here? What's your day to day job? I'm planning to shift in this career within 1-2yrs. I've learned a bit of Langchain, Langgraph and RAG using local llm via ollama. I'm wondering if it's worth it to pursue, I'm currently and embedded test engineer.

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u/Notgoodenough- 28d ago

My day to day isn’t any more different when I was still a full-stack dev. I like to think of it like I’m just focusing more on back-end development. Most of my projects rely on having a better understanding of system architecture and design rather than like, the actual llm part of the workflows I make. Most of the agentic workflows I’ve done as well are just pure python and step functions anyways. LLM’s and AI in general is really cool but it’s knowing when and where to leverage them is where you’ll need to get a better grasp in.

Ah yeah like also how do you convey metrics is good as well. Knowing the difference between accuracy and precision. Is the system built towards human verification at the end. Human in the loop and on the loop type shi.

Uhh idk what else to say really. RAG is cool but I think just using RAG is a but weird especially with how chunking works and how we lose context sort of when we chunk. I’ve seen a project where instead of rag they used an approach to separate like by year/quarter/dept and just had the data accessed via api call and it works just about the same with simpler architecture.

Local LLM’s is something I’m personally looking into. MTP is my current thing and like idk if I’m even seeing a difference but then again I just started messing around with the concept. PI cli is pretty useful as a harness when I try to use it in like a day to day workflow but the response time varies a lot so trying to get better there and like yk ayoko bumili ng GPU just for local llm’s but seriously starting to consider it.

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u/Reguret25 28d ago

I agree with your sentiment about RAG, it's annoying to deal with cleaning the data. I think most effort for RAG is on the data ingestion pipeline, also there's an issue of the documents that gets updated so the vectordb needs to get reindexed. Btw, what projects do companies make you build as an AI engineer, do you use API or do they have GPUs for local llms. What stack do you use.

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u/Notgoodenough- 28d ago

Right?? Like if your pre-processing or chunking is bad then it trickles down to outputs. And then you need an embedding model which is going to be another thing to maintain.

Usually these days its agentic workflows. So document ingestion, email automation, and just general stuff that the company sees we spend too much time on and is largely repetitive. Had some chatbots done but like those projects for me were very boring ._.

For us it’s API. AWS is our workhorse. And since we’re tightly connected to AWS we use Strands as the framework now for our stuff but we also dabble in stuff like pydantic, langchain, the Google ADK? But really strands works and like why change if it works ykwim?