AI Automation Architect
About the Role We are building an internal AI system that acts as a persistent strategic brain, content engine, and project coordinator. This is not a chatbot role and not a prompt-writing role. This is a systems architecture role. Your job is to design and implement the infrastructure that allows multiple AI agents to: -Remember past work and decisions -Route tasks intelligently -Improve over time through feedback -Surface all activity in one clear control panel If successful, this system will eliminate repetition, reduce cognitive overhead, and allow our work to compound instead of reset. What You’ll Build In this role, you’ll design and implement the core systems that allow our AI agents to function as a reliable, persistent, and improving system. You will be responsible for: 1. Persistent Memory Building a long-term, structured memory layer for agents Creating a canonical knowledge base for rules, preferences, frameworks, and decisions Implementing retrieval of relevant past context to inform new tasks 2. Agent Orchestration Designing routing logic to assign requests to the appropriate agent Assembling the right context from memory and the knowledge base for each task Capturing and storing agent outputs with appropriate metadata 3. Central Dashboard (Notion-based initially) Designing and implementing a dashboard that shows: Requests, projects, outputs, feedback, and knowledge base entries Creating clear views for: “In Review” “Active” “Approved” “Memory Updates” Enabling simple actions such as creating requests, approving outputs, and triggering training updates 4. Feedback & Training Loop Implementing an approve / revise / reject workflow Automatically updating memory based on edits, feedback, and decisions Ensuring traceability between requests, outputs, feedback, and memory updates 5. Reliability & Maintainability Implementing logging, error handling, and retry mechanisms Adding simple cost and usage controls Producing clear documentation so the system can be maintained and extended Responsibilities Build persistent memory for multiple AI agents Integrate agents with Notion and other tools Design and implement a central dashboard Create feedback loops so agents improve over time Prevent context loss and duplication Maintain documentation and system clarity Optimize for reliability and simplicity Preferred Stack n8n or Make for orchestration Notion API for dashboard and knowledge base Supabase + pgvector or similar for vector memory OpenAI / Anthropic APIs Optional: Slack or email integration Required Experience Proven experience building end-to-end automation systems Experience integrating AI APIs into real workflows Strong systems thinking and architecture judgment Experience with Notion, Airtable, or similar as structured systems At least one implementation of retrieval-augmented generation (RAG) or vector memory Clear documentation habits What Success Looks Like New request → agent output appears in dashboard automatically Agents stop forgetting because memory is updated continuously All work-in-progress and approved outputs are visible in one place Weekly improvement in output quality due to feedback-driven learning Engagement Structure Initial contract: 6–10 weeks 15–25 hours per week Goal: deliver a working Phase 1 system Opportunity to extend or deepen engagement after Phase 1 Compensation $30-60/hr depending on experience Final rate depends on experience and demonstrated capability Apply tot his job