Lead AI Engineer – Agentic & Generative AI (DFW Area)

Posted 4 Days Ago
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Richardson, TX, USA
Hybrid
123K-209K Annually
Senior level
Real Estate • Software • PropTech
RealPage is a leading SaaS provider for the multifamily and rental housing industry.
The Role
Leads the strategy, architecture, and delivery of agentic and generative AI platforms. Designs scalable systems using foundation models, RAG, multi-agent workflows, retrieval technologies, and AI observability. Establishes reusable AI services, evaluation and governance standards, and responsible AI practices. Mentors AI engineers and data scientists, partners with executives and product stakeholders, and manages performance, reliability, security, and cost optimization for production AI systems.
Summary Generated by Built In
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 a Lead AI Engineer who is a senior technical leader responsible for driving the strategy, architecture, and delivery of Agentic and Generative AI solutions across our PropTech portfolio. You will define and implement the technical roadmap for AI systems, mentor the AI engineering team, and collaborate with executives and product leaders to identify high-impact AI opportunities.


You will design robust, scalable AI platforms that leverage foundation models, RAG, multi-agent systems, and emerging technologies to create differentiated experiences for our customers.


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


Responsibilities
  • Technical Strategy & Architecture
    • Own the end-to-end architecture for AI products and platforms:
      • Model selection strategy (Google vs. OpenAI, small vs. large models)
      • Multi-agent and workflow orchestration patterns (responder/thinker pattern, tool calling, agentic frameworks)
      • Data and retrieval architecture (RAG, hybrid search, knowledge graphs, semantic caching)
    • Evaluate and introduce emerging technologies such as:
      • Next-generation LLMs and multimodal models
      • Real-time streaming infrastructures
      • Advanced agent frameworks, workflow engines (e.g., Agents SDK, Google ADK,  LangGraph, etc.)
  • Platformization & Reusable Capabilities
    • Design and lead the implementation of shared AI services and SDKs:
      • Reusable RAG pipelines and ingestion frameworks
      • Common UI components and design patterns for AI copilots and agents
      • Modular reusable coding practices for agentic back-end processes
    • Establish standards and best practices for:
      • Prompt design and versioning
      • Model and retrieval evaluation
      • Observability, logging, and incident response for AI systems.
  • Leadership & Mentoring
    • Provide hands-on technical leadership to AI Engineers, ML Engineers, and Data Scientists:
      • Guide architectural decisions and code quality
      • Conduct thorough design and code reviews
      • Mentor team members in LLMs, RAG, agentic design, and production AI practices
    • Help define and grow the AI engineering culture, focusing on innovation, quality, and responsible AI.
  • Delivery & Stakeholder Management
    • Partner closely with Product, Design, and Business stakeholders to:
      • Identify high-value AI use cases aligned with company strategy and PropTech domain needs
      • Shape product roadmaps and define measurable success criteria for AI initiatives
    • Lead complex, cross-functional AI projects from concept to production, ensuring:
      • Clear requirement definitions and project plans
      • On-time delivery with high quality and reliability
      • Ongoing iteration based on user feedback and metrics.
  • Evaluation, Governance & Responsible AI
    • Define robust evaluation frameworks:
      • Offline and online metrics for relevance, safety, user satisfaction, and business impact
      • Human evaluation workflows for complex or sensitive tasks
    • Drive AI governance and responsible AI practices:
      • Content safety, bias and fairness considerations, PII handling
      • Compliance with internal policies and external regulations (e.g., GDPR-like requirements, data residency)
    • Collaborate with security, privacy, and legal teams to ensure compliant AI solutions.
  • Performance, Reliability & Cost Management
    • Lead performance and cost optimization for AI systems:
      • Model routing, distillation, and caching strategies
      • Right-sizing infrastructure and making build-vs-buy decisions
      • SLAs/SLOs for key AI services, including latency, uptime, and error budgets.
    • Proactively identify and mitigate technical risks related to scalability, data quality, or vendor lock-in.
    Qualifications
    • Required Knowledge / Skills / Abilities

      • Typically 8+ years of experience in Software Engineering, ML Engineering, or Data Science, with 3+ years hands-on in Applied AI/LLMs and at least 2+ years in a senior/lead role.
      • Deep expertise in:
        • Python and TypeScript/JavaScript in production environments
        • Designing and operating distributed, cloud-native systems (GCP, Azure, or AWS)
        • Containerization and orchestration (Docker, Kubernetes) and modern CI/CD.
      • Working with coding assistants like Windsurf, Cursor, Codex, etc.
      • Proven track record of:
        • Architecting and shipping complex AI systems to production at scale
        • Leading multi-engineer initiatives and mentoring others
        • Making data-driven tradeoffs between speed, quality, and cost.
      • Advanced experience with:
        • LLM-based application design (prompting, tool use, function calling, multi-agent workflows)
        • RAG architectures, vector databases, and retrieval optimization techniques
        • AI observability, monitoring, and evaluation frameworks.
      • Excellent communication and stakeholder management skills:
        • Ability to communicate complex AI concepts to executives and non-technical partners
        • Comfortable representing AI strategy and progress to leadership and cross-functional teams.

      Nice-to-Have Skills / Abilities

      • Experience with:
        • Working with coding assistants like Windsurf, Cursor, Codex, etc.
        • Multimodal and real-time agents (voice + text + UI control, streaming interactions).
      • Background in:
        • AI experiment tracking and evaluation frameworks (e.g., OpenAI Evals, Langsmith Evals, etc.) 
        • Data platforms (data lakes/warehouses, feature stores, event streams like Kafka)
        • Browser automation software such as PlayWright
        • Designing AI products in domains with strong regulatory or privacy constraints.
      • Experience building organizational AI strategies, setting standards, and helping define AI hiring and capability roadmaps. #LI-JL1 
    • In this role you would be expected to come into the office 2-3 days a week. 

    #LI-HYBRID #LI-JL1 

    Pay RangeUSD $122,600.00 - USD $208,800.00 /Yr.

    Skills Required

    • Typically 8+ years of experience in Software Engineering, ML Engineering, or Data Science
    • At least 3+ years of hands-on experience in Applied AI or LLMs
    • At least 2+ years in a senior or lead role
    • Deep expertise with Python and TypeScript or JavaScript in production environments
    • Experience designing and operating distributed, cloud-native systems on GCP, Azure, or AWS
    • Experience with Docker, Kubernetes, and modern CI/CD
    • Track record architecting and shipping complex AI systems to production at scale
    • Experience leading multi-engineer initiatives and mentoring others
    • Experience making data-driven tradeoffs among speed, quality, and cost
    • Advanced experience with LLM application design, prompting, tool use, function calling, and multi-agent workflows
    • Advanced experience with RAG architectures, vector databases, and retrieval optimization
    • Experience with AI observability, monitoring, and evaluation frameworks
    • Excellent communication and stakeholder management skills
    • Experience with coding assistants such as Windsurf, Cursor, or Codex
    • Experience with multimodal and real-time agents
    • Experience with AI experiment tracking and evaluation frameworks such as OpenAI Evals or LangSmith Evals
    • Experience with data lakes, data warehouses, feature stores, or event streams such as Kafka
    • Experience with browser automation software such as Playwright
    • Experience designing AI products in regulated or privacy-constrained domains
    • Experience building organizational AI strategies and defining AI hiring and capability roadmaps

    RealPage, Inc. Compensation & Benefits Highlights

    The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about RealPage, Inc. and has not been reviewed or approved by RealPage, Inc..

    • Leave & Time Off Breadth — Time off is positioned as flexible in some salaried/exempt roles, with vacation, sick time, floating holidays, and “take what you need”/unlimited-style PTO described. Parental leave and adoption assistance are also framed as part of the standard time-off and family-leave offering.
    • Healthcare Strength — Health coverage is presented as comprehensive, spanning medical, dental, vision, and pharmacy plans along with mental-health resources and an EAP. Additional wellness components like fitness reimbursement and on-site amenities appear available in some locations.
    • Strong & Reliable Incentives — Variable compensation can be attractive in certain quota-carrying roles when targets are attainable, with on-target earnings ranges described as clear for some sales positions. Performance-based bonuses and other role-specific incentives are also described as available in parts of the organization.

    RealPage, Inc. Insights

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    The Company
    HQ: Richardson, TX
    8,000 Employees
    Year Founded: 1998

    What We Do

    RealPage is the leading global provider of AI-enabled software platforms to the real estate industry. By using RealPage solutions for operational excellence in the front office and back office, many leading property owners, operators and investors gain transparency into asset performance with data insights, enhancing experiences with customized tools and improving efficiencies to generate incremental yield. Founded in 1998 and headquartered in Richardson, Texas, RealPage joined the Thoma Bravo portfolio of market-leading enterprise software firms in 2021 to realize faster growth and innovation in serving more than 24 million rental units from offices in North America, Europe and Asia. RealPage has been certified as a Great Place to Work™ in Colombia, India, the Philippines, the UK and the U.S. For more information, visit https://www.RealPage.com. Industry verticals: Conventional, Enterprise, Institutional, Affordable HUD, Student Living, Military Housing, Tax Credit, Senior Living, Single Family, Vacation Rentals, Commercial

    Why Work With Us

    At RealPage, we want to provide value to all we serve – from business to business, to rental residents, to our rock-star teammates, to the communities where they live and work.

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