About the Project AACE (Autonomous Agentic Commerce Engine) is moving e-commerce from Software-as-a-Service to Software-as-Labor. We are building a digital workforce of autonomous agents that don't just "chat," but execute complex operational workflows (inventory rebalancing, dynamic pricing, and logistical resolution) via direct API orchestration. The MVP is live. The architecture is built. I am a solo founder who has built this through disciplined, 15-hour daily sprints. I am now looking for a "force-multiplier"—a brilliant engineer to help move the system from "Human-in-the-Loop" to full autonomy. The Mission We are not building another chatbot wrapper. We are building an orchestration layer for the automated economy. You will be responsible for developing the "nervous system" of our agents, ensuring they can reason through non-deterministic environments while maintaining deterministic reliability. Technical Stack Language: Python (Expert level required). Frameworks: LangGraph, CrewAI, or LangChain (Stateful orchestration experience is a must). LLMs: Deep experience with GPT-4o, Claude 3.5 Sonnet, and fine-tuning open-source models (Llama 3/Mistral). Integrations: Shopify API, Stripe API, AWS Lambda, and Pinecone/Milvus for Vector memory. Infrastructure: AWS (Compute optimization for high-inference loads). What You Will Be Doing Architecting Multi-Agent Flows: Designing state-machines that allow agents to "handoff" tasks to one another (e.g., a Support Agent handing off a logistical error to an Operations Agent). Tool Integration: Building robust, fail-safe "Tools" (API wrappers) that agents can call to modify real-world databases (Shopify/ERP). Latency Optimization: Minimizing the "time-to-action" for agentic reasoning loops. Guardrail Engineering: Implementing logic-gated verification to ensure agents never execute an incorrect API call (e.g., preventing an accidental $10,000 refund). Data Synthesis: Helping build the pipeline that takes "Human-in-the-Loop" parameters and converts them into autonomous planning data. Who You Are (The "High-Signal" Candidate) The "Full-Stack" AI Mind: You understand both the high-level reasoning of LLMs and the low-level "plumbing" of APIs and databases. Extreme Ownership: You prefer a 15-hour day of deep work over a 5-hour day of meetings. You are disciplined, focused, and self-managed. Systems Thinker: You don't just write functions; you think about how data flows through a stateful system. Problem Solver: When an LLM hallucinations or a logic loop breaks, you have the patience and technical depth to debug the "why." Work Conditions & Compensation Engagement: Long-term, high-intensity partnership. Hours: Flexible, but we move fast. I am looking for someone who treats this as their primary obsession. Rate: [Insert your hourly or monthly range, e.g., $50–$120/hr based on expertise]. Growth: For the right person, this role can evolve into a Founding Engineer / CTO position as we scale and close our institutional round. How to Apply (The Filter) Standard "copy-paste" applications will be ignored. To prove you are the right fit, please answer the following: Describe the most complex Stateful AI Agent or Multi-Agent workflow you have built. How did you handle state management? How do you prevent LLM Hallucinations when an agent is given permission to hit a "Write" API (like issuing a refund or changing a price)? We operate with a high degree of discipline (15-hour blocks). What is your preferred "deep work" schedule, and how do you maintain focus on complex technical builds? Include the word "ORCHESTRATOR" at the top of your cover letter so I know you read the full post.