Asks for

The ad says“Experience building agentic AI systems — multi-step workflows where AI takes actions, not just answers questions — using frameworks like LangGraph, Semantic Kernel, OpenAI's or Anthropic's agent SDKs, or equivalent”
The ad says“Experience building agentic AI systems — multi-step workflows where AI takes actions, not just answers questions — using frameworks like LangGraph, Semantic Kernel, OpenAI's or Anthropic's agent SDKs, or equivalent”
The ad says“Experience building with cloud AI services - e.g. Azure AI Foundry (including Azure OpenAI), and Azure AI Search, or their AWS/GCP equivalents”
The ad says“Experience building with cloud AI services - e.g. Azure AI Foundry (including Azure OpenAI), and Azure AI Search, or their AWS/GCP equivalents”
The ad says“Experience building with cloud AI services - e.g. Azure AI Foundry (including Azure OpenAI), and Azure AI Search, or their AWS/GCP equivalents”
The ad says“Experience building with cloud AI services - e.g. Azure AI Foundry (including Azure OpenAI), and Azure AI Search, or their AWS/GCP equivalents”
The ad says“You understand data governance, identity management, and permissions in an enterprise environment”
The ad says“Hands-on experience with modern data platforms - e.g. Microsoft Fabric, Databricks, Snowflake or similar”
The ad says“You understand data governance, identity management, and permissions in an enterprise environment”
The ad says“Experience building agentic AI systems — multi-step workflows where AI takes actions, not just answers questions — using frameworks like LangGraph, Semantic Kernel, OpenAI's or Anthropic's agent SDKs, or equivalent”
The ad says“Hands-on experience with modern data platforms - e.g. Microsoft Fabric, Databricks, Snowflake or similar”
The ad says“Hands-on experience with modern data platforms - e.g. Microsoft Fabric, Databricks, Snowflake or similar”
The ad says“Experience building agentic AI systems — multi-step workflows where AI takes actions, not just answers questions — using frameworks like LangGraph, Semantic Kernel, OpenAI's or Anthropic's agent SDKs, or equivalent”
The ad says“You understand data governance, identity management, and permissions in an enterprise environment”
The ad says“Experience building agentic AI systems — multi-step workflows where AI takes actions, not just answers questions — using frameworks like LangGraph, Semantic Kernel, OpenAI's or Anthropic's agent SDKs, or equivalent”
The ad says“Hands-on experience with modern data platforms - e.g. Microsoft Fabric, Databricks, Snowflake or similar”

RRA Capital | Phoenix, AZ

RRA Capital is a real estate credit platform focused on structured lending and opportunistic investments, powered by a lean, high-performing team with direct access to decision-makers.

RRA Culture and Core Values

We value intellectual curiosity, ownership, and people who are genuinely enjoyable to work with.

Enjoyable to Be Around – Team-oriented, professional, and ego-free.
Passionate About Continuous Improvement – Committed to self-growth and feedback.
Smart – Creative, efficient, and solutions-driven—not academic.
Reliable – Self-starters with a deep sense of ownership and follow-through.

If you thrive in an entrepreneurial environment and are excited to contribute to a firm that’s growing with purpose and discipline, we’d love to hear from you.

Reach out to Lisa Donovan or apply at rracapital.com.
#LI-LD1

AI & Data Architect

Most AI roles at this level ask you to maintain what someone else built. This one asks you to build it.

We're hiring our first AI and Data Architect — the person who designs and builds the data foundation that will power how we invest, operate, and eventually deploy intelligent agents across the firm.

There is not much of a stack to inherit. No committee to slow you down. No ten layers of approval. Just direct access to leadership, and the autonomy to build it right.

What you'll own:

You'll start by understanding our data — where it lives, what it means, how it moves across Microsoft 365, HubSpot, underwriting files, loan documents, emails, and market research. Then you'll build the foundation: a unified knowledge layer with enterprise search, clean governance, and secure permissions. From there, the work hypothesis moves toward AI copilots for our investment and operations teams, and eventually an agent-first operating model, harnessing AI to build an "appified" RRA experience.

The 24-month outcome we're building toward: enterprise search across firm knowledge, a trusted data layer connecting our core systems, AI copilots deployed to business teams, and a meaningful reduction in manual workflows.

You'll translate that vision into architecture. Then you'll build it.

What we're looking for:

You don't need 15 years. You need to be genuinely excellent — the kind of person who has already built things that work in production, not just in demos. If you're earlier in your career and your work speaks for itself, we want to hear from you.

Specifically:

Hands-on experience with modern data platforms - e.g. Microsoft Fabric, Databricks, Snowflake or similar
Experience building with cloud AI services - e.g. Azure AI Foundry (including Azure OpenAI), and Azure AI Search, or their AWS/GCP equivalents
You know the difference between a working prototype and a production-grade system — and you've shipped the latter
Experience building agentic AI systems — multi-step workflows where AI takes actions, not just answers questions — using frameworks like LangGraph, Semantic Kernel, OpenAI's or Anthropic's agent SDKs, or equivalent
You understand data governance, identity management, and permissions in an enterprise environment
You can operate independently — there's no large engineering team here, and that's intentional

Financial services experience is a plus, not a requirement. Intellectual curiosity about how a real estate credit firm actually works — how deals get evaluated, structured, and closed — matters more.

Phoenix-based is strongly preferred. Exceptional candidates in New York City will be considered.

Why this seat is different:

You won't be one of fifty engineers working on a feature. You'll be the architect of an entire firm's data and AI foundation — with your name on every major decision. The problems are real, the access is direct, and the upside of building something that works is visible immediately.

Compensation is designed to attract top-tier technical talent. Benefits include medical insurance, 401(k) with employer match, and unlimited PTO.