Senior AI Architect / Engineer – AI Agents, Agent Operators, Prompting & Private LLM (Long-Term)

Job Description We are a fast-growing car dealership looking to transform our operations using AI. We are seeking a highly experienced AI Architect / Senior AI Engineer to design and implement a complete AI-driven ecosystem across our business. This includes AI agents, agent operators, advanced prompting systems, and a private LLM infrastructure. This is a high-impact, long-term project. We are not looking for experimentation—we want someone who can design, build, and scale real AI systems in production. Objectives Your mission will be to help us: - Automate internal workflows and operational processes - Build and deploy AI agents and agent operators - Design advanced prompting systems and agent logic - Implement a private/internal LLM system (secure, no data leakage) - Reduce operational costs using AI (including coding agents) - Improve efficiency, response time, and decision-making - Integrate AI into our existing systems (CRM, DMS, APIs, etc.) Scope of Work 1. AI Architecture - Design a scalable AI architecture (cloud or hybrid) - Define agent orchestration layers and tool usage - Recommend models, frameworks, and infrastructure - Ensure strong security and data privacy 2. AI Agents & Agent Operators - Build intelligent systems including: - Task-based AI agents (sales, support, operations) - Agent operators / orchestrators that manage multiple agents - Tool-using agents (API calls, database access, workflows) - Memory-enabled agents (short-term + long-term context) Use cases include: - Sales / BDC (lead follow-up, appointment booking, call flows) - Customer communication (chat, SMS, email automation) - Operations (reporting, internal workflows) - Internal automation (task execution, document handling) 3. Prompt Engineering & Agent Logic - Design robust prompting frameworks (not just simple prompts) - Implement: - Structured prompts - Tool calling / function calling - Guardrails & validation layers - Optimize prompts for: - Accuracy - Cost - Reliability 4. Private LLM - Deploy a self-hosted or secure LLM setup - Implement RAG (Retrieval-Augmented Generation) - Build internal AI for: - Knowledge base - Document processing - Coding assistant 5. Automation & Integration - Integrate with CRM / DMS / APIs - Connect marketing platforms (Meta, Google) - Build automation pipelines (Make, n8n, or custom backend) 6. Development Optimization - Implement AI-assisted development workflows - Use coding agents to reduce dev cost - Improve internal developer productivity Requirements - Proven experience building AI systems in production - Strong experience with AI agents and agent orchestration - Deep experience in prompt engineering / prompt systems design - Experience with LLMs (OpenAI, Claude, LLaMA, Mistral, etc.) - Experience with self-hosted / private LLM setups - Experience with RAG, embeddings, vector databases - Strong backend/system architecture skills - Experience in the car industry field Bonus - Experience with agent frameworks (LangChain, LlamaIndex, etc.) - Voice AI (Twilio, call automation) - Automotive / dealership experience - DevOps / MLOps experience - AI cost optimization at scale Engagement - Long-term collaboration - Start with architecture + MVP, then scale - Flexible (hourly or milestone-based) Final Note: We are looking for someone who thinks in systems, agents, automation, and scale—not just someone who uses AI tools. If you have built real AI infrastructure and understand agent operators + prompting at a deep level, we want to work with you.