AI Data Engineer III

Overview

• Make an Impact with RealPage

• Looking for a role where your work directly influences business outcomes and customer success?

At RealPage, you'll join a global SaaS technology company that is transforming the real estate industry through innovative software, data, and AI-driven solutions. We empower our teams to think big, take ownership, and deliver meaningful results every day.

• Whether you're solving complex challenges, collaborating with global stakeholders, or driving operational excellence, you'll have the opportunity to grow your career while making a real impact.

What You'll Do

This role reports into Director/Sr. Manager within Technology GRC and is the technical builder behind the function's agentic AI transformation. The AI Data Engineer III designs, builds, and operates the data pipelines, AI agents, and automations that deliver GRC services — with primary focus on the Data Governance capabilities (e.g., data quality, data lineage and data catalog), all operating under a human-in-the-loop model supervised by the responsible GRC leader.

The role bridges GRC domain requirements and engineering execution: building the data foundations (ingestion, modeling, quality) that agentic workflows depend on, and prototyping control automations, evidence collectors, and governance tooling that reduce manual effort and enable the team to scale without proportional headcount growth.

Responsibilities

• GRC Tool & Automation Engineering

• Build and integrate agentic AI solutions and automations within the enterprise GRC platform to standardize workflows, automate evidence collection, and improve reporting.

• Develop control automations, evidence collectors, and governance tooling, reducing dependence on the broader engineering backlog.

Risk Register Automation

• Engineer AI-assisted workflows to populate, maintain, and reconcile the enterprise Risk Register across technology domains.

• Automate linkage between risk entries, controls, and remediation tracking.

Policy Governance Automation

• Build AI-assisted tooling for policy drafting, framework crosswalks, annual review cadence, and exception workflows.

Agent Design, Safety & Operations (Human-in-the-Loop)

• Design agentic workflows using RAG, function/tool calling, and Model Context Protocol (MCP), with appropriate guardrails for accuracy, confidentiality, and IP boundaries.

• Implement human-in-the-loop checkpoints and monitoring so GRC leaders can supervise and validate agent outputs.

• Apply AI risk controls aligned to OWASP Top 10 for LLM Applications, NIST AI RMF, ISO/IEC 42001, and MITRE ATLAS.