About this opportunity
RealPage lists this Senior Software Engineer (Solutions) - TypeScript/Node.js/React opportunity in richardson, Texas. Review the employer’s description below for duties, qualifications and application requirements.
Job description
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
Required Knowledge / Skills / Abilities
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.
Pay Range
USD $125,700.00 - USD $213,900.00 /Yr.
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.
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.
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Worksite address
richardson, TX, 75080, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.