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Our MVP mobile app is live. Now we're upgrading the brain.
We are looking for a backend-focused Agentic AI engineer to architect and implement a smarter multi-agent system powered by Retrieval-Augmented Generation (RAG) and structured user context.
This is not a chatbot wrapper job.
This is about building an intelligent, evolving AI system.
What You'll Work On
Your mission: Make our AI Mentor smarter, proactive, and more context-aware.
You will:
Design and implement a multi-agent architecture
Build a RAG pipeline connected to:
Structured onboarding data
User journals
Habit & streak data
Categorized knowledge base
Connect agents to Supabase (Postgres + vector store)
Implement long-term memory & user profiling logic
Implement agent roles (we have them working already separately )
Optimize prompt orchestration and context injection
Improve personalization & proactive cron job logic
The mobile app is built in React Native.
Your focus is backend + AI system architecture.
Supabase (Postgres + vector embeddings)
OpenAI APIs
React Native frontend
Structured knowledge base
Ideal Candidate
Strong experience building RAG systems
Experience with multi-agent AI architectures
Backend development experience
Deep understanding of:
Prompt engineering
Context windows & memory handling
Vector databases
Embeddings & retrieval optimization
Experience working with structured + unstructured data
Clean architecture mindset (scalable & maintainable)
You think in systems and design before coding.
You understand LLM behavior deeply and use AI daily
If you've built something like:
AI copilots
Personal AI assistants
RAG-based production systems
Context-aware multi-agent pipelines
We want to talk
To Apply Please include:
Examples of RAG or agent-based systems you've built
Your approach to designing a scalable AI memory system
How you would structure multi-agent orchestration for a coaching app
Your availability (hours/week)
Contract duration of less than 1 month. with 30 hours per week.
Mandatory skills: Artificial Intelligence, agentic, Supabase, Mobile App, React Native, API, Database Architecture
Sprachkenntnisse
- English
Hinweis für Nutzer
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