Contact person: Medical AI Diagnostics Platform

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Location: Brisbane, Australia

Budget: Recommended by industry experts

Time to start: As soon as possible

Project description:
"Fractional CTO / AI Engineer – Veterinary Evidence Platform (VEP)

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About the Project

We’re building VEP — a clinical evidence platform for veterinarians that works like OpenEvidence for human medicine.
The MVP will allow vets to:
• Search trusted veterinary journals & guidelines
• Retrieve and summarise peer-reviewed evidence
• Get results with inline citations and links to sources
• Filter by species, study type, and date

We’re looking for a high-end, hands-on AI/engineering leader who can architect, build, and deploy this MVP in ~3 months.

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Role Overview

This is a contract / fractional CTO role — perfect for a senior engineer who has led AI search or RAG-based product builds.
You’ll take full ownership of:
• Designing the tech stack
• Implementing the ingestion & retrieval pipeline
• Integrating an LLM for summarisation
• Deploying a production-ready web app

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Core Responsibilities
• Architecture & Planning: Define the MVP scope, tech stack, and deployment plan.
• Data Ingestion: Build automated ingestion from PubMed, Crossref, Unpaywall, and veterinary guideline sites (ACVIM, AAHA, WSAVA, etc.).
• Search & Retrieval: Implement a hybrid search pipeline (BM25 + vector search) with filtering for species, study type, and date.
• LLM Integration: Build a Retrieval-Augmented Generation (RAG) system that summarises findings with inline citations and links.
• Frontend MVP: Deliver a simple, intuitive search interface for vets.
• Deployment: Host on a scalable, secure environment (e.g., AWS, GCP, Azure).
• Handover: Provide documentation so the platform can be extended by a future team.

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Required Skills & Experience
• 5+ years in software engineering, with a focus on AI/ML/NLP systems
• Strong experience in RAG pipelines and vector databases (e.g., pgvector, Pinecone, Weaviate)
• Proven track record with API integrations (PubMed, Crossref, Unpaywall, etc.)
• Proficient in Python (FastAPI/Flask) and modern JS frameworks (React/Vue) for frontend
• Experience deploying on AWS/GCP/Azure
• Strong grasp of prompt engineering and LLM safety best practices
• Ability to work independently and deliver production-quality code quickly
• Bonus: Experience with medical or veterinary data pipelines" (client-provided description)