AI Agent Developer, HR

Lennar is hiring an AI Agent Developer, HR to design, build, deploy, and maintain intelligent AI agents that improve corporate workflows and decision-making. The role embeds with business teams to identify use cases, develop production-ready agents, support adoption, and contribute field learnings to the enterprise AI roadmap.

Responsibilities:

• Embed directly with corporate function teams: shadowing Associates, mapping how work actually gets done, and partnering with product owners, business analysts, and engineers to scope high-impact AI agent use cases
• Serve as an AI advisor to function leaders: presenting recommendations, framing trade-offs and risks in business terms, and building the confidence that moves teams from curiosity to committed adoption
• Design agent personas, roles, and workflows, including decision logic, triggers, escalation paths, and human-in-the-loop rules
• Build and configure AI agents using LLMs, retrieval-augmented frameworks, orchestration tools, and relevant APIs, integrating them with internal systems, data sources, and external services
• Develop robust prompt engineering strategies, tool invocations, memory and context management, and monitoring mechanisms so agents act effectively and reliably
• Deliver working prototypes and live demos early and often, using rapid feedback from business partners to shape each agent well before it reaches production
• Test, iterate, and validate agent behavior under real-world conditions through unit tests, scenario simulations, edge-case handling, and performance and safety monitoring
• Deploy agents into production environments and establish observability through logs, metrics, and usage dashboards, along with versioning, drift detection, and lifecycle management
• Maintain agents post-deployment by refining prompts, tuning models, and improving workflows, while championing adoption through Associate training, enablement materials, user guides, and change logs
• Ensure governance, compliance, security, and ethical considerations are built into agent design, including data access, audit trails, output safety, and escalation protocols
• Track and report the measures that prove value, hours returned, cycle time reduced, quality improved, and bring field learnings back to the enterprise as reusable patterns and best practices