AI Engineer

RYZ Labs

12d

About The Position

Ryz Labs is seeking an AI Engineer to work with a client in the real estate investment industry. The client develops AI-powered solutions that automate and optimize investment processes, including deal sourcing, financial analysis, due diligence, and portfolio monitoring, for real estate investment funds, institutional investors, and family offices.

This is an AI engineering role with a forward-deployed focus. The engineer will build the core AI systems—including agents, pipelines, and evaluation infrastructure—and deploy solutions with clients. The role involves working directly with real estate investors to solve complex problems, owning production code through deployment, and partnering with the go-to-market team to scope, build, and implement solutions. Lessons learned from client deployments will inform and improve the platform.

Requirements

• At least 3 years of experience shipping production software, ideally using Python and/or TypeScript.
• Deep hands-on experience building LLM applications in production, including agents, RAG, tool use, evaluation, and context engineering; experience with LangGraph, LlamaIndex, MCP, or similar is relevant.
• Strong understanding of the AI landscape, including model selection and trade-offs among accuracy, cost, and speed.
• Solid machine-learning fundamentals, including evaluation, problem decomposition, and judgment about when not to use an LLM.
• Track record as a builder, such as a founding engineer, early startup hire, ex-founder, or ex-CTO, or experience on a top engineering team with end-to-end ownership of outcomes.
• Comfort working directly with clients, explaining technical trade-offs to fund partners, and then building the solution.
• Fast, pragmatic approach, with a preference for shipping working solutions over perfecting diagrams.
• Cloud fundamentals in AWS, GCP, or Azure; data pipeline experience; and awareness of enterprise security, including data isolation, access controls, and not training on client data.
• Comfort working across UK and GCC hours.

Responsibilities

• Build multi-step agents, tool-use capabilities, and workflows for investment tasks such as sourcing, underwriting, due diligence, investment committee memos, and portfolio monitoring.
• Own the AI stack, including RAG and document pipelines, model routing across frontier and open models, prompt and context engineering, and structured outputs for Excel and investment committee formats.
• Build evaluation and observability systems to measure accuracy, cost, latency, and reliability, and ensure financial figures can be traced back to their sources.
• Build reusable connectors, data pipelines, and components to make subsequent client deployments faster.
• Work directly with clients to scope, build, and deploy AI solutions in partnership with the go-to-market team.
• Feed knowledge gained from client deployments back into the platform.

What This Job Offers

• Job Type: Full-time
• Education Level: No Education Listed