Senior AI Enginee-Skin Analysis, Personalized Analytics, RAG & LLM Integration

We're developing an AI-powered skin health and wellness application and are looking for an experienced AI engineer to help design and implement the more complex AI components. The project already has a React Native mobile application, Supabase backend, and an early-stage Next.js dashboard. An existing development team is responsible for the core backend and application development. We're looking for someone who can focus specifically on AI architecture, implementation, integration, and evaluation while collaborating with our existing developers and technical leads. Key Responsibilities 1. AI Skin Analysis Integrate a licensed third-party skin analysis/vision API. Implement image quality checks and confidence handling. Support historical scan comparisons and progress tracking. Handle uncertain results, failed scans, and provider limitations. 2. Personalized Pattern Engine Analyze historical skin observations alongside lifestyle, sleep, stress, skincare routines, and treatment data. Develop deterministic algorithms for personal baselines, longitudinal comparisons, and pattern identification. Account for incomplete data, time windows, and confounding factors. Generate explainable insights without unsupported medical or causal claims. 3. RAG Pipeline Build a retrieval-augmented generation system using approved educational and scientific content. Implement document processing, chunking, embeddings, vector search, and source citations. Support content versioning, retrieval evaluation, and evidence-grounded responses. Ensure unverified user-generated content is not treated as authoritative evidence. 4. AI Assistant and LLM Integration Combine authorized user history, scan results, pattern-engine outputs, and retrieved knowledge. Implement structured LLM responses, safety guardrails, and fallback handling. Support personalized educational guidance and user-confirmed actions. Prevent unsupported medical diagnoses and recommendations. 5. AI Architecture, Integration & Testing Review the existing architecture and recommend practical improvements. Collaborate with the current backend and application developers. Define AI service interfaces, API contracts, and data requirements. Implement AI-specific monitoring, logging, performance optimization, and evaluation. Support production readiness and technical documentation. Existing Technology Stack React Native Next.js Supabase / PostgreSQL Python / FastAPI or Node.js OpenAI, Anthropic, or similar LLM providers RAG, embeddings, and vector databases Third-party computer vision APIs We're open to your recommendations for the AI-specific architecture and tools. Project Status The application is already under development. This is not a complete rebuild. The existing team will continue handling the core application, frontend, and general backend development. Your primary focus will be the AI components and their integration. The exact state of existing AI functionality will be confirmed during an initial architecture review. What We're Looking For Strong production experience with LLMs, RAG, and AI backend architecture. Experience building personalized analytics or longitudinal data-processing systems. Experience integrating computer vision or image-analysis APIs. Strong Python/FastAPI or Node.js backend development skills. Familiarity with privacy-sensitive applications and secure data handling. Ability to work independently while collaborating with an existing engineering team. Experience with healthcare or wellness applications is a plus. Initial Deliverables We'd like to begin with an architecture and requirements review, followed by a detailed implementation estimate. Please provide: Your relevant AI engineering experience and examples of similar production systems. Your recommended technical approach for the four main AI components. Your hourly rate and availability. We're looking for someone who can build reliable, maintainable AI systems, not just connect an LLM API.