We are seeking a senior AI developer to build and enhance AI models for our business. The role involves developing, testing, and deploying AI solutions, as well as improving existing models to increase accuracy and performance. The ideal candidate should have strong experience in AI development and be able to work independently on complex projects.

We are a small residential real estate investment company seeking an AI Solutions Architect to enhance our acquisition platform. The role involves designing and implementing AI solutions to improve data analysis and decision-making processes. The ideal candidate will have experience in AI architecture and a strong understanding of real estate data analysis.

Overview We run an AI voice assistant for self-storage operators. We have an internal, AI-assisted workflow for triaging call feedback — investigating what happened on a call, diagnosing the root cause in our codebase, and drafting fixes. We’re looking for someone technical to run that AI-assisted workflow day to day and help us make it better. You’ll be driving AI coding agents, reading real code to understand behavior, and improving the process and tooling itself. What you’ll do Use our AI agent tooling to work through a queue of customer feedback on AI voice calls. Read our TypeScript/Node codebase (voice-agent prompt assembly, workflow/“SOP” engine, tool implementations) to diagnose why the agent behaved a certain way — not just guess. Draft fixes: workflow-instruction edits, knowledge-base entries, or code changes via pull request with a clear verification plan. Improve the triage process itself — refine the AI agent prompts/skills, conventions, and the internal MCP tooling that powers it. Write clear, customer-facing summaries of what changed for our team to review and approve. You’re a great fit if you Read and reason about code confidently — ideally TypeScript/Node; React a plus. Have hands-on experience driving AI coding agents (Claude Code, Cursor, or similar) and understand how LLM prompts/tools/agents fit together. Think in cause-and-effect: “the agent did X because line Y / instruction Z.” Write precisely and concisely for both technical and non-technical audiences. Are process-minded — you spot the repetitive thing and turn it into a better workflow. Bonus: prompt engineering, LLM tool/agent development, or voice/conversational AI experience. How we work We’ll start with a paid trial on a small batch, then scale steady ongoing volume. To apply: Tell us about a time you used an AI coding agent to diagnose or fix something non-trivial in a codebase you didn’t write — what you did, and how you verified it worked. A link to relevant work is a plus.

About the Role We're looking for an experienced AI/ML developer to design, build, and deploy production-grade AI systems. You'll work on LLM-powered applications, retrieval-augmented generation (RAG) pipelines, and multi-agent architectures. This is a hands-on role for someone who has shipped real AI products—not just prototypes. Responsibilities Design and implement RAG pipelines (chunking, embeddings, vector stores, retrieval optimization) Build multi-agent systems using LangChain and LangGraph Integrate and fine-tune LLMs (OpenAI, Anthropic, open-source models) Develop and optimize prompts, tool-calling, and agent orchestration logic Deploy scalable, reliable AI services with proper monitoring and evaluation Collaborate on architecture decisions and code reviews Required Skills (Mandatory) Strong AI/ML fundamentals and hands-on experience Proven LLM application development RAG pipeline design and optimization LangChain and LangGraph (production experience) Agent / multi-agent system build experience Vector databases (Pinecone, Weaviate, Chroma, FAISS, or similar) Python (production-level) API integration (OpenAI, Anthropic, Hugging Face) Nice to Have Fine-tuning / LoRA / model optimization Cloud deployment (AWS/GCP/Azure) MLOps and evaluation frameworks (LangSmith, RAGAS) Experience with streaming, caching, and cost optimization