Only for Experts: Backend Dev for Medical AI – PubMed, DrugBank, OpenAI -- 2
Budget: €750 – €1,500 EUR
Backend Developer Needed for AI-Powered Clinical Platform (OpenAI, PubMed, DrugBank)
We’re looking for a highly skilled backend developer with solid experience in artificial intelligence to help us optimize and expand the infrastructure of Novik, a cutting-edge AI platform that supports dentists in clinical decision-making.
Important: Please do not apply unless you have proven experience working with AI platforms and backend architecture. We've had several setbacks with candidates lacking the necessary expertise. We’re only interested in developers who can demonstrate real-world experience in this domain.
What You’ll Be Working On Multilingual Support:
Fix Google OAuth registration system The current Google authentication system fails to complete user registration properly. Both the frontend (React) and backend (Django) configurations should be reviewed.
Ensure that redirect URIs, client ID, and client secret are properly set in the Google Cloud Platform console. The goal is to allow users to register and log in using Google seamlessly and
securely.
Ensure that the AI responds in the same language as the user (primarily English and Spanish).
Knowledge Base Priority: Fine-tune backend logic to prioritize our internal clinical protocols and knowledge base before relying on general AI outputs. Protocol Integration: Ensure stable and consistent access to predefined dental protocols for safer, more accurate responses.
PubMed Integration: Automatically retrieve relevant articles (from the last 5 years) based on patient history, current medication, and proposed treatments. Format all references using the Vancouver style with superscript citations.
DrugBank Data Access: Query drug data without API access — ideally by scraping or other automated methods — including dosages, max doses, and clinical usage info.
Dynamic Dosage Engine: Implement logic that adjusts drug recommendations based on age, weight, comorbidities, and polypharmacy. API Optimization:
We currently use OpenAI's API but are open to alternative models (e.g., Anthropic, Mistral) if they offer better control or cost-efficiency. Ideal Candidate Strong backend development skills (Python/Django or Node.js preferred). Solid experience integrating AI APIs (OpenAI, Claude, etc.) and managing prompt flows. Familiarity with PubMed API and non-API web scraping (e.g., for DrugBank).
Experience with structured clinical data, citation formatting, and safety-critical applications. Proactive communicator and problem-solver. Bonus if you have domain knowledge in healthcare or dentistry. Deliverables Backend with improved performance, structure, and maintainability. Seamless PubMed and DrugBank integration. Optimized AI response pipeline with protocol and knowledge base prioritization. Robust multilingual handling. Logging, documentation, and error handling for long-term scalability.
We’re looking for a highly skilled backend developer with solid experience in artificial intelligence to help us optimize and expand the infrastructure of Novik, a cutting-edge AI platform that supports dentists in clinical decision-making.
Important: Please do not apply unless you have proven experience working with AI platforms and backend architecture. We've had several setbacks with candidates lacking the necessary expertise. We’re only interested in developers who can demonstrate real-world experience in this domain.
What You’ll Be Working On Multilingual Support:
Fix Google OAuth registration system The current Google authentication system fails to complete user registration properly. Both the frontend (React) and backend (Django) configurations should be reviewed.
Ensure that redirect URIs, client ID, and client secret are properly set in the Google Cloud Platform console. The goal is to allow users to register and log in using Google seamlessly and
securely.
Ensure that the AI responds in the same language as the user (primarily English and Spanish).
Knowledge Base Priority: Fine-tune backend logic to prioritize our internal clinical protocols and knowledge base before relying on general AI outputs. Protocol Integration: Ensure stable and consistent access to predefined dental protocols for safer, more accurate responses.
PubMed Integration: Automatically retrieve relevant articles (from the last 5 years) based on patient history, current medication, and proposed treatments. Format all references using the Vancouver style with superscript citations.
DrugBank Data Access: Query drug data without API access — ideally by scraping or other automated methods — including dosages, max doses, and clinical usage info.
Dynamic Dosage Engine: Implement logic that adjusts drug recommendations based on age, weight, comorbidities, and polypharmacy. API Optimization:
We currently use OpenAI's API but are open to alternative models (e.g., Anthropic, Mistral) if they offer better control or cost-efficiency. Ideal Candidate Strong backend development skills (Python/Django or Node.js preferred). Solid experience integrating AI APIs (OpenAI, Claude, etc.) and managing prompt flows. Familiarity with PubMed API and non-API web scraping (e.g., for DrugBank).
Experience with structured clinical data, citation formatting, and safety-critical applications. Proactive communicator and problem-solver. Bonus if you have domain knowledge in healthcare or dentistry. Deliverables Backend with improved performance, structure, and maintainability. Seamless PubMed and DrugBank integration. Optimized AI response pipeline with protocol and knowledge base prioritization. Robust multilingual handling. Logging, documentation, and error handling for long-term scalability.