AI Architect I

🔥 3 minutes ago

🤠 Texas – Remote

🤠 Texas – Remote

💵 $177.5k - $322.5k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 AI Engineer

👻 Ghost score 0%

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RealPage, Inc.

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

💼 Consulting

📦 Logistics

📣 Marketing

💰 $18.6M Post-IPO Equity - RealPage on 2022-01

Consulting • Logistics • Marketing

RealPage, Inc. is a provider of property management software and services focused on the rental housing and broader real estate markets. The company offers cloud-based (SaaS) platforms and AI-driven tools for leasing, resident experience, revenue and financial management, utility and sustainability, vendor and spend management, smart building integrations, and analytics—serving multifamily, affordable, student, senior, single-family and commercial property operators. RealPage’s solutions are designed for property management companies, owners, investors and vendors to streamline operations, increase revenue, and improve the resident experience.

📋 Description

• Design end-to-end architectures for agentic AI solutions, including orchestration, runtime execution, workflow management, tool invocation, system integrations, evaluation, observability, and supportability. • Translate product requirements, business workflows, and customer use cases into technical designs and implementation plans. • Define reusable patterns for multi-step agent behavior, task routing, handoffs, cross-system interactions, state management, and multi-agent coordination. • Partner with AI Platform teams to use shared orchestration, runtime, evaluation, reporting, monitoring, and developer-tooling capabilities. • Collaborate with engineering teams through architecture reviews, design guidance, technical documentation, and production-readiness assessments. • Evaluate tradeoffs involving scalability, reliability, performance, security, maintainability, cost, developer experience, and delivery speed. • Define integration patterns for APIs, enterprise systems, data sources, tools, model services, and Model Context Protocol capabilities. • Establish observability requirements, including logging, metrics, traces, dashboards, alerts, debugging workflows, and operational reporting. • Partner with QA/Eval teams on evaluation criteria, regression coverage, testing strategies, and quality controls. • Support release planning, launch-readiness reviews, production monitoring, incident response, and post-release improvement. • Identify repeated solution patterns and recommend shared product or platform capabilities. • Contribute to architecture standards, reference designs, technical decision records, implementation guidance, and reusable documentation. • Help teams apply responsible AI, privacy, security, governance, and human oversight requirements. • Communicate technical decisions, dependencies, risks, and recommendations to engineering, product, operations, and business stakeholders.

🎯 Requirements

• Experience designing or building backend systems, distributed applications, workflow platforms, integration services, developer platforms, cloud applications, or AI-enabled solutions. • Working knowledge of APIs, asynchronous processing, service coordination, event-driven architectures, stateful systems, and enterprise integrations. • Understanding of architecture principles related to scalability, reliability, performance, availability, maintainability, security, and production support. • Familiarity with LLM-based applications, AI agents, retrieval techniques, prompt and context management, tool calling, workflow automation, or model-driven products. • Ability to convert business and workflow requirements into practical technical architectures. • Experience with cloud services, deployment pipelines, monitoring, logging, dashboards, and production troubleshooting. • Understanding of testing, evaluation, regression coverage, release readiness, and operational support for production systems. • Ability to evaluate technical alternatives and explain architecture tradeoffs to technical and nontechnical stakeholders. • Strong written and verbal communication skills, including the ability to produce clear diagrams, design documents, decision records, and implementation guidance. • Strong collaboration skills across engineering, product, QA/Eval, security, infrastructure, operations, and support teams. • Ability to work effectively in an evolving technical environment. • Preferred: experience designing or implementing production LLM applications, AI agents, workflow automation, or intelligent assistant solutions. • Preferred: familiarity with agent orchestration frameworks, model gateways, evaluation frameworks, vector search, retrieval-augmented generation, and AI observability. • Preferred: experience integrating AI solutions with enterprise platforms, internal services, APIs, data sources, and third-party tools. • Preferred: familiarity with Model Context Protocol, tool integration primitives, structured outputs, agent memory, workflow state, and multi-agent patterns. • Preferred: experience with responsible AI practices, including safety controls, access management, data protection, human oversight, and auditability. • Preferred: experience creating reusable reference architectures, platform patterns, technical standards, or architecture governance. • Preferred: familiarity with production incident management, reliability engineering, deployment strategies, and post-release support. • Relevant cloud, software architecture, data, security, or AI certifications are beneficial but not required.

🏖️ Benefits

• 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. • Certain roles are eligible for additional rewards, including annual bonus and sales incentives depending on the applicable plan, role, and individual performance.