Sr. AI Architect (DFW Area)

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 Sr. AI Architect who is a senior technical leader who provides end-to-end technical direction for our Agentic & Generative AI ecosystem across the RealPage platform. You will define the reference architectures, patterns, and guardrails that enable teams to safely and efficiently build AI-powered products in the PropTech domain.You will work at the intersection of AI, data, and platform engineering—shaping how we use LLMs, RAG, agentic frameworks, and emerging multimodal capabilities at scale. You’ll partner with product and engineering leadership to translate business strategy into an AI architecture roadmap, enabling multiple delivery teams to build on a coherent, secure, and observable AI platform.Enterprise AI Architecture & StrategyDefine the overarching AI architecture for RealPage:Standard patterns for RAG, multi-agent systems, and workflow orchestrationIntegration with existing microservices, data platforms, and event-driven systems.Create and own AI reference architectures, blueprints, and design patterns that individual product teams can adopt and extend.Evaluate and recommend vendors and technologies across:Model providers (OpenAI, Anthropic, Google, xAI, Meta, Mistral, etc.)Vector databases (pgvector, Pinecone, Weaviate, Qdrant , etc.)Agent frameworks and orchestration tools (Agents SDK, Google ADK, LangChain, workflow engines like n8n, Zapier, etc.) Platformization & Shared CapabilitiesOwn 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)Define and champion approaches for:Semantic caching, cost optimization, and latency reductionMulti-tenant, domain-isolated AI use across RealPage products. Data, Retrieval & Knowledge ArchitecturePartner with Data/Analytics teams to align AI architecture with data strategy:Data sourcing from warehouses/lakes, operational databases, event streams.Governance for which data can be used in training, retrieval, and inference.Architect robust RAG and knowledge systems:Taxonomies and metadata standardsImplement knowledge retrieval process that draws from multiple sources and uses reranking to improve the response quality.Long-context models, memory systems, and potential use of knowledge graphs / vector-native databases.Define ingestion and refresh strategies to keep AI knowledge current and trustworthy. Security, Compliance & Responsible AIDefine architectural guardrails for:Data privacy, PII redaction, and tenant isolationEncryption, key management, and secure connectivity to model providersOn-prem / VPC deployments for sensitive workloads where required.Collaborate with Security, Privacy, and Legal teams to define policies and patterns for:Content safety, toxicity filtering, and jailbreak resistanceAuditability and traceability of AI decisions (logs, traces, model versions, prompts, and responses).Establish a Responsible AI framework in partnership with leadership:Guidelines for fairness, bias mitigation, and explainability where appropriateReview processes for high-risk AI features. Observability, Evaluation & MLOpsArchitect end-to-end observability for AI systems:Traces and spans for prompts, model calls, tool calls, and RAG steps (e.g., OpenTelemetry, LangSmith).Metrics for latency, cost, error rates, and model-specific KPIs.Define standard evaluation approaches:Offline evaluation harnesses for RAG and LLM tasks (e.g., Ragas, TruLens, custom eval suites).Online experimentation patterns (A/B tests, feature flags, canary releases).Work with MLOps/Platform Engineering to:Integrate AI workflows into CI/CD and deployment pipelines Technical Leadership & Cross-Functional CollaborationProvide architectural leadership to AI Engineers, ML Engineers, and product teams:Support solution design for critical AI features and platforms.Conduct design reviews and guide trade-offs (build vs. buy, Google ADK vs. OpenAI SDK).Partner with Product leaders to:Identify high-leverage AI opportunities based on our data and capabilitiesTranslate business strategies into a prioritized, feasible AI roadmap.Act as a key technical representative for AI architecture in discussions with senior leadership and external partners.Typically10+ yearsexperience in Software Engineering / ML Engineering / Data Platforms, with3+ yearsin applied AI/ML and2-3+ yearsin an architect/principal or equivalent role.Working with coding assistants like Windsurf, Cursor, Codex, etc.Deep experience designing and operating cloud-native systems onAWS, GCP, or Azure, including:Kubernetes, Docker, service meshes, API gatewaysCI/CD pipelines and infrastructure-as-code (Terraform, CloudFormation, etc.).Strong expertise in:PythonandTypeScript/JavaScriptecosystemsModern architectural styles (microservices, event-driven, serverless, domain-driven design).Proven track record architecting and delivering production AI/LLM systems:LLM integration (APIs and/or self-hosting), tool calling, and multi-step/agentic workflowsRAG architectures, vector databases, and retrieval optimization at scaleRobust observability and evaluation practices for AI-driven products.Strong understanding of:Data architecture (data lakes/warehouses, streaming, batch pipelines)Security and compliance considerations for AI (identity, access control, tenant isolation, PII/PHI).Excellent communication and leadership:Comfortable engaging with executives, product leaders, and engineering teamsAble to create clear architectural documentation, roadmaps, and decision records.Nice-to-Have Skills / AbilitiesExperience with:Multimodal and real-time agents (voice, vision, document understanding, OCR, streaming interactions).Background in:Building internal platforms or Centers of Excellence for AIEstablishing architectural governance (ADR processes, reference implementations, tech standards).AI in regulated or data-sensitive environments (finance, healthcare, housing, etc.).Familiarity with:AI product management concepts (user research, experimentation, metrics for AI features)Emerging AI stack components (guardrail frameworks, AI-native workflow engines, semantic routers).Browser automation software such as PlayWright.SALARY AND BENEFITSRealPage 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.USD $157,600.00 - USD $268,400.00 /Yr.

Created: 2026-03-07