AI Engineer ( Freelancer/Consultant)
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 1d ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 33d ago
The date the source published, not the day we noticed it (2026-08-13). Last seen at its source just now.
Is it remote?
Marked remote on the employer's board
Their board carries a remote setting on this posting — a field they filled in, not wording we read. The location field names somewhere specific, which is usually where the team or the entity sits.
Who may apply?
India
The description states no restriction of its own. This is the source's own tag.
Pay not stated
Similar roles pay $6,750–7,250/mo
Middle 50% of 9 listings that do state pay — Engineering · all levels · India · USD/month. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
workable employer's own board first seen 11d ago · last seen just now
The listing
This role is for one of Weekday’s clients
Min Experience: 5+ years
Location: Remote
JobType: full-time
What You'll Do
- Build LLM, RAG, and agentic AI systems from the ground up
- Design and implement document intelligence pipelines
- Work hands-on with LangChain, LangGraph, and LlamaCloud
- Deploy and scale AI services across AWS, GCP, or Azure
- Ship production-ready solutions quickly, without compromising on quality
Requirements
What We're Looking For
- Strong, demonstrable experience in GenAI / LLM-based systems
- Solid backend expertise in Python, with FastAPI or Django
- Hands-on experience with RAG, embeddings, and vector databases
- Exposure to ML, MLOps, and model evaluation practices
- Comfortable working independently, with strong ownership and minimal oversight
Must-have skills
Python, RAG, Generative AI
Good-to-have skills
Artificial Intelligence, LLM, LangChain