Backend Engineer Required – AI Document Processing Platform (Not WordPress / Not No-Code)
Budget: $3,000 – $5,000 AUD
Please read carefully before bidding.
We are building a production-grade AI-powered building inspection report platform. 90% was built in base44 however, base44 cannot parse pdf"s larger than 10MB, so we have hit a roadblock and decided to take another route.
This is NOT:
*A WordPress job
*A Shopify job
*A bubble/no-code job
*A “prompt engineering” job
*A basic CRUD web app
This is a serious backend architecture project involving:
PDF parsing (11MB+ technical reports)
AI defect extraction
Structured data normalization
Repair cost estimation logic
Long-running job orchestration
Background workers / queues
Multi-user concurrency
Production deployment architecture
NOTE: Required Technical Stack (Non-Negotiable)
You must have experience with:
Node.js or Python backend (FastAPI / Express / NestJS)
Background job queues (BullMQ / Celery / Redis / RabbitMQ)
PostgreSQL
Object storage (S3 or equivalent)
Production deployment (AWS / DigitalOcean / similar)
API architecture design
Handling long-running async workflows
Bonus:
Experience with AI APIs (OpenAI / Anthropic)
Experience with document parsing
Cost optimisation for AI workloads
NOTE: The Core Challenge
We process building inspection PDFs (50–70+ defects per document).
Each defect requires:
AI classification
Structured extraction
Cost estimation logic
Controlled pricing variance (not wide AI guesses)
The system must:
Handle multiple reports processing simultaneously
Avoid timeouts
Avoid race conditions
Avoid pricing inconsistencies
Maintain state safely across long workflows
NOTE: DO NOT APPLY IF:
You primarily build WordPress sites
You are a UI/UX designer only
You rely fully on AI to generate your code
You cannot explain how to design a job queue system
You have never deployed a backend to production
You respond with generic copy-paste proposals
NOTE: To Be Considered, Your Proposal MUST Include:
A short explanation of how you would architect long-running PDF processing
What job queue system you would use and why
How you would prevent AI pricing variance issues
Links to similar backend systems you’ve built (real production links)
If you do not answer these specifically, your proposal will be ignored.
NOTE: Project Stage
We have:
Full functional specification
Frontend prototype
AI processing logic concept
Database model draft
We now need:
A serious backend engineer to implement this properly.
NOTE: Important
We are not looking for the cheapest developer.
We are looking for someone who understands:
Scalable architecture
Async processing
Production reliability
AI integration properly
If you are that person, we would love to work long-term.
We are building a production-grade AI-powered building inspection report platform. 90% was built in base44 however, base44 cannot parse pdf"s larger than 10MB, so we have hit a roadblock and decided to take another route.
This is NOT:
*A WordPress job
*A Shopify job
*A bubble/no-code job
*A “prompt engineering” job
*A basic CRUD web app
This is a serious backend architecture project involving:
PDF parsing (11MB+ technical reports)
AI defect extraction
Structured data normalization
Repair cost estimation logic
Long-running job orchestration
Background workers / queues
Multi-user concurrency
Production deployment architecture
NOTE: Required Technical Stack (Non-Negotiable)
You must have experience with:
Node.js or Python backend (FastAPI / Express / NestJS)
Background job queues (BullMQ / Celery / Redis / RabbitMQ)
PostgreSQL
Object storage (S3 or equivalent)
Production deployment (AWS / DigitalOcean / similar)
API architecture design
Handling long-running async workflows
Bonus:
Experience with AI APIs (OpenAI / Anthropic)
Experience with document parsing
Cost optimisation for AI workloads
NOTE: The Core Challenge
We process building inspection PDFs (50–70+ defects per document).
Each defect requires:
AI classification
Structured extraction
Cost estimation logic
Controlled pricing variance (not wide AI guesses)
The system must:
Handle multiple reports processing simultaneously
Avoid timeouts
Avoid race conditions
Avoid pricing inconsistencies
Maintain state safely across long workflows
NOTE: DO NOT APPLY IF:
You primarily build WordPress sites
You are a UI/UX designer only
You rely fully on AI to generate your code
You cannot explain how to design a job queue system
You have never deployed a backend to production
You respond with generic copy-paste proposals
NOTE: To Be Considered, Your Proposal MUST Include:
A short explanation of how you would architect long-running PDF processing
What job queue system you would use and why
How you would prevent AI pricing variance issues
Links to similar backend systems you’ve built (real production links)
If you do not answer these specifically, your proposal will be ignored.
NOTE: Project Stage
We have:
Full functional specification
Frontend prototype
AI processing logic concept
Database model draft
We now need:
A serious backend engineer to implement this properly.
NOTE: Important
We are not looking for the cheapest developer.
We are looking for someone who understands:
Scalable architecture
Async processing
Production reliability
AI integration properly
If you are that person, we would love to work long-term.
Related categories:
Python
Software Architecture
Node.js
PostgreSQL
Redis
Database Development
Docker
API
Backend Development
FastAPI