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Open nowPosted 311 days ago

AI Engineer (DFW Area)

RealPage, Inc.93 open roles

Pay
$107,200 – $182,600 a year
Where
Richardson, Texas, United States
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Your applicationOpen nowAI Engineer (DFW Area)RealPage, Inc. · Richardson, Texas, United States

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The clock on this job

Early applications get read.

12.3% of postings close within 7 days. Measured by our own scanner across the market. RealPage, Inc. postings stay open a median of 1 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.3%7 days
  4. 19.3%14 days
  5. 35.6%30 days
  6. 57.8%60 days
This job: posted 311 days ago

RealPage, Inc. median: 1 days open

The posting

Overview

RealPage is at the forefront of the Generative AI revolution, dedicated to shaping the future of artificial intelligence within the Property Tech domain. Our Agentic AI team is focused on driving innovation by building next generation AI applications and enhancing existing systems with Generative AI capabilities.

We are seeking an AI Engineer to help us with the development, deployment, and scaling of advanced AI applications that address real-world challenges. In this role, you will focus on designing, building, and scaling advanced AI applications in the PropTech space. You will work with state-of-the-art foundation models, RAG architectures, and multi-agent systems while partnering closely with product, design, and engineering teams.

You will be responsible for taking AI concepts from ideation to production, owning end-to-end solutions that improve our products and transform user experiences.

In this role you would be expected to come into the office 2-3 days a week.

Responsibilities

  1. Agentic AI & Generative Application Engineering
  • Evaluate and use LLMs and multimodal models from multiple providers (e.g., OpenAI, Google, Anthropic, etc.) for:
  • Conversational assistants, task-based copilots, and AI agents
  • Summarization, content generation, document understanding, generative analytics
  • Basic multimodal use cases (text + image, text + document, and soon video/audio)
  • Design and implement agentic workflows (e.g., tool-calling, multi-step reasoning, multi-agent orchestration) using:
  • LangChain, OpenAI Agents SDK, Google ADK or similar frameworks.
  1. Prompt Engineering & Guardrails
  • Design and optimize prompts and system instructions to:
  • Improve task completion, reliability, and latency
  • Minimize hallucinations and toxic/unsafe outputs
  • Implement structured outputs (JSON/JSON Schema)
  • Develop function/tool calling and prompts that help AI call them properly
  • Integrate safety/guardrail layers (e.g., content moderation APIs, Guardrails AI, Rebuff, custom policies) to keep conversations focused
  1. RAG & Knowledge Integration
  • Architect and implement RAG pipelines:
  • Choose and configure vector databases (e.g., PGVector, Vertex AI Search, Pinecone, etc.)
  • Build ingestion pipelines for internal data (documents, tickets, logs, property data, etc.)
  • Implement knowledge retrieval process that draws from multiple sources and uses reranking to improve the response quality.
  • Explore emerging retrieval techniques (semantic caching, knowledge graphs, long-context models, memory systems).
  1. Full-Stack & System Integration
  • Build or integrate front-end experiences (React / Vue / Svelte / Web RTC) for AI agents and copilots.
  • Develop back-end services to orchestrate AI calls using REST, gRPC, WebSockets, or MCP; ensure scalability and observability.
  • Integrate with internal systems and PropTech data sources using secure APIs and data contracts.
  1. Evaluation, Monitoring & Optimization
  • Design and maintain evaluation pipelines and benchmarks for LLM-based features:
  • Offline metrics (accuracy, relevance, latency, cost)
  • Human-in-the-loop evaluations where needed
  • Use AI observability and tracing tools (e.g., LangSmith, OpenTelemetry, etc.) to monitor quality.
  • Optimize for performance, reliability, latency, and cost through:
  • Model selection and routing (e.g., small vs. large models, Google vs. OpenAI)
  • Prompt/token optimization and caching strategies.
  1. Collaboration, Documentation & Delivery
  • Collaborate with cross-functional teams (Product, Design, Domain Experts, Data Science, Platform Engineering) to define requirements and success metrics.
  • Participate in architecture and design reviews; write clear technical documentation and runbooks.
  • Contribute to shared libraries, templates, and best practices for AI development.
  • Work in an Agile environment and own features from design through deployment and maintenance.

Qualifications

  • 5+ years of total experience in Software Engineering and/or Data Science, with at least 2 years focused on Generative AI/LLMs.
  • Degree in Computer Science, Machine Learning, Data Science, or related field, or equivalent practical experience.
  • Strong proficiency in:Python for AI/ML, data pipelines, and back-end services JavaScript/TypeScript for front-end and/or Node services SQL and experience working with relational databases and basic data modeling
  • Working with coding assistants like Windsurf, Cursor, Codex, etc.
  • Proven experience building production-grade software:Writing clean, testable, maintainable code Using CI/CD pipelines, code reviews, and Git workflows
  • Hands-on experience with:At least one agentic/orchestration framework (OpenAI Agents SDK, Google ADK, LangChain, etc.) LLM APIs and/or open-source models (e.g., via OpenAI, Google, Hugging Face, Ollama) Vector embeddings, vector databases, and RAG architectures
  • Experience with one or more major cloud platforms (GCP, Azure, and AWS) and:Docker for containerization Kubernetes or a managed container service (e.g., EKS, GKE, AKS)
  • Strong communication skills and ability to collaborate with both technical and non-technical stakeholders.

Nice-to-Have Skills / Abilities

  • Experience with:
  • Voice-enabled AI agents (STT, TTS, WebRTC, Twilio Voice, Socket.IO, VAPI)
  • Multimodal models (e.g., GPT models including Realtime, Gemini Pro Vision, etc.)
  • Orchestrating multiple models (routing, ensembles, fallback strategies)
  • Familiarity with:
  • AI experiment tracking and evaluation frameworks (e.g., OpenAI Evals, Langsmith Evals, etc.)
  • Feature stores, data versioning (e.g., Feast, DVC), and MLOps workflows
  • Browser automation software such as PlayWright
  • Background in:
  • AI security, privacy, and compliance (PII handling, SOC2, GDPR considerations)
  • A/B testing and online experimentation for AI features.

In this role you would be expected to come into the office 2-3 days a week. #LI-JL1 #LI-HYBRID

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.

Pay Range

USD $107,200.00 - USD $182,600.00 /Yr.

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