Agentic AI Developer IV

Agentic AI Developer IV

LocationUS-TX-RichardsonID2026-14363

Category Engineering Position Type Regular

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 IV 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 to establish patterns that can scale beyond one team or use case.

Engineering Team Enablement

Work directly with engineering teams, champions, and internal stakeholders to help them adopt AI effectively.

Responsibilities include

Pairing with teams on AI use cases and implementation patterns

Providing technical 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 AI enablement sessions

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 to identify and deliver high-impact AI use cases.

Responsibilities include

Translating engineering productivity needs into AI-enabled solutions

Supporting roadmap-aligned internal AI initiatives

Contributing to adoption and capacity-improvement goals

Helping measure the impact of AI enablement efforts

Communicating technical concepts clearly to engineering and non-engineering audiences

Performance, Reliability, and Cost Awareness

Design AI solutions with practical performance and cost considerations, including:

Model selection and routing

Prompt and context optimization

Caching and retrieval efficiency

Latency and reliability considerations

Build-vs-buy recommendations

Avoidance of vendor lock-in where practical

Qualifications

Typically 6+ years of software engineering experience, with meaningful hands-on experience building production applications or internal platforms.

2+ years of applied AI, LLM, Generative AI, or agentic workflow experience.

Strong programming experience in Python, TypeScript/JavaScript, or similar production languages.

Experience designing and building cloud-native applications or services in Azure, GCP, or AWS.

Practical experience with

LLM-based application development

Prompt engineering and prompt versioning

Tool calling / function calling

RAG architectures

Vector databases or semantic retrieval

Multi-step workflow or agent orchestration

Familiarity with modern software engineering practices, including

CI/CD

Git-based development

Automated testing

API design

Observability and logging

Experience using or enabling AI coding tools such as GitHub Copilot, Cursor, Windsurf, Codex, or similar tools.

Ability to work directly with engineering teams to understand needs, prototype solutions, and drive adoption.

Strong communication skills with the ability to explain AI concepts and implementation patterns clearly.

Nice-to-Have Skills / Abilities

Experience building internal developer platforms, engineering productivity tools, or enablement frameworks.

Experience with agent frameworks or orchestration tools such as LangGraph, OpenAI Agents SDK, Google ADK, Semantic Kernel, CrewAI, or similar frameworks.

Experience with evaluation frameworks such as OpenAI Evals, LangSmith Evals, RAGAS, or custom evaluation harnesses.

Experience with browser automation or workflow automation tools such as Playwright.

Experience with knowledge management, internal documentation systems, or enterprise search.

Experience working in environments with privacy, compliance, or regulated-data considerations.

Background in enterprise software, PropTech, fintech, or other complex business domains.

Experience supporting AI adoption programs, engineering champions, office hours, or internal technical enablement.

SALARY AND BENEFITS

RealPage provides a competitive salary package along with a comprehensive benefit plan that includes:

Health, dental, and vision insurance.

Retirement savings plan with company match.

Paid time off and holidays.

Professional development opportunities.

Performance-based bonus based on position.

#LI-JK1 #LI-REMOTE

Compensation may vary depending on your location, qualifications including job-related education, training, experience, licensure, and certification, that could result at a level outside of these ranges. Certain roles are eligible for additional rewards, including annual bonus, and sales incentives depending on the terms of the applicable plan and role as well as individual performance.

Equal Opportunity Employer

RealPage Company is an equal opportunity employer and committed to creating an inclusive environment for all employees.

Pay Range

USD $159,100.00 - USD $270,900.00 /Yr.