Contract
Full-stack LLM engineer — multimedia recommendation / document workflow
Deadline not provided — verify source
Full-stack AI document-processing and RAG MVP
Project evidence involving React, Python, FastAPI. First observed 6 Sept 2026; the response opens on upwork.com.
- Budget
- $500.00 fixed price
- Work format
- Project
- Role family
- Software specialist
- Seniority
- Level not stated
- Observed
- 6 Sept 202659 days old
- Deadline status
- Deadline not provided — verify source
- Response destination
- upwork.com
Opportunity summary
Full-stack AI document-processing and RAG MVP. The source classifies this as project work involving React, Python, FastAPI, PostgreSQL, pgvector, Redis, Docker, GitHub Actions, AWS, OpenAI API, RAG, Python/FastAPI + OpenAI + pgvector, React/Next.js + FastAPI, AWS + Docker + GitHub Actions. Location or remote eligibility: Worldwide remote Upwork listing; agency eligibility not published.
Technology and scope
The reported stack is Python, FastAPI/Django, React, PostgreSQL, Redis/Celery, pgvector/Pinecone, LangChain/LangGraph, OpenAI/Anthropic/Bedrock, Docker, AWS, GitHub Actions. Check the source for required versions, deliverables and which technologies are mandatory.
Engagement details
Project: a defined delivery outcome rather than an open-ended employment relationship. Source timing: 7 calendar days; one-time project; contract-to-hire option
Budget
Source budget wording: $500.00 fixed price. Confirm the currency, unit, scope and payment terms before preparing a proposal.
Dates and availability
First observed by Leadiy on 6 Sept 2026, 11:31 UTC. Public since 20 Sept 2026, 00:30 UTC. Deadline not provided — verify source. A listed deadline does not confirm that applications are still accepted. These are observation and publication dates, not a reconstruction of the source posting date. Date-only deadlines have no supplied timezone; the date changes here at midnight UTC.
Related market context
In the current 30-day Hiring Pulse, React appears in 55 of 325 observed opportunities (16.9%). Counts are multi-label, so one opportunity may contribute to several technology buckets. This is a separate aggregate sample, not a confirmation of this opportunity’s availability.
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