Agentic AI Developer III

Overview RealPage is accelerating the adoption of Generative AI and agentic engineering practices across its technology organization. The Internal AI Center of Excellence is responsible for enabling engineering teams to apply AI effectively, safely, and consistently across the software development lifecycle. We are seeking an AI Developer III to help design, build, and scale internal AI solutions that improve engineering productivity, accelerate delivery, and support RealPage’s AI adoption goals. This role will focus on developing reusable AI patterns, agentic workflows, internal developer tools, reference implementations, and enablement assets that help engineering teams move from experimentation to repeatable production use. The ideal candidate is a hands‑on AI engineer with strong software development experience, practical knowledge of LLMs and agentic systems, and the ability to partner with engineering teams to turn AI concepts into usable internal capabilities. Responsibilities Internal AI Solution Development Design and build internal AI solutions that support engineering productivity and software delivery, including: AI-powered developer workflows and assistants Agentic SDLC automation patterns Internal tools for code analysis, documentation, testing, migration, and engineering support Reusable prompt, tool-calling, and workflow patterns Reference implementations that can be adopted by engineering teams Develop solutions that are practical, scalable, maintainable, and aligned with RealPage engineering standards. Agentic Workflow and Platform Enablement Build reusable capabilities that help teams adopt AI consistently across the organization, including: Multi-step agentic workflows Tool-calling and orchestration patterns RAG-based internal knowledge solutions Shared SDKs, templates, and integration examples Reusable components for copilots, agents, and AI-enabled engineering workflows Partner with senior architects and engineering leaders toestablishpatterns that can scale beyond one team or usecase. Engineering Team Enablement Work directly with engineering teams, champions, and internal stakeholders to help them adopt AI effectively. AI Evaluation, Quality, and Responsible Use Help define and apply practical evaluation and governance practices for internal AI solutions, including: Prompt and workflow evaluation Accuracy, relevance, and usefulness testing Safety and responsible AI considerations PII and sensitive-data handling Logging, observability, and feedback loops Human-in-the-loop review patterns where appropriate Ensure internal AI solutions are developed with quality, security, privacy, and reliability in mind. Delivery and Cross-Functional Collaboration Partner with engineering leadership, product teams, architecture, security, and other stakeholders toidentifyand deliver high-impact AI use cases. Responsibilities include: Pairing with teams on AI use cases and implementation patterns Providingtechnical guidance on LLM, RAG, and agentic workflow design Supporting proof-of-concept efforts and helping mature them into repeatable practices Creating playbooks, examples, templates, and documentation for internal engineering use Participating in office hours, workshops, and #J-18808-Ljbffr RealPage