RealPage

Sr. AI Platform Engineer

RealPage$105K — $180K *
Enterprise Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • 8-10 years of engineering experience with 7+ years on cloud platforms.
  • 2-3 years experience using AI coding tools for automation.
  • Strong experience with GCP/AWS and relevant deployment technologies.
  • Working knowledge of authentication and authorization frameworks.
  • 4+ years of scripting and automation experience with Python or JavaScript.
  • Ability to architect secure hosting for open-source LLMs.

Responsibilities

  • Define deployment patterns for AI agents and secure architectures.
  • Automate buildouts, standardize releases, and manage environments.
  • Operate AI platform services with incident response and monitoring.
  • Collaborate with teams to establish AI governance and security standards.
  • Coach engineers and guide project implementations.

Benefits

  • Health, dental, and vision insurance.
  • Retirement savings plan with company match.
  • Paid time off and holidays.
  • Professional development opportunities.
  • Performance-based bonus potential.
Full Job Description
Overview

This Senior Engineer turns RealPage's responsible agentic factory strategy into repeatable infrastructure, automated delivery pipelines, production-grade operating practices, and clear engineering standards. The role blends hands-on AI platform delivery with governance, observability, secure deployment, and mentoring across technical teams. 

Responsibilities

Core Responsibilities 

  • Define standards-based deployment patterns for responsible AI agents, reusable platform capabilities, and secure agent runtime architectures, including identity, access, and secrets management. 
  • Automate AI platform buildout, release standardization, environment provisioning, CI/CD, Terraform/Helm deployments, and operational runbooks. 
  • Operate reliable AI platform services with incident response, capacity planning, OpenTelemetry traces/logs/metrics, monitoring, rollback, and disaster recovery practices. 
  • Collaborate across InfoSec, CloudOps, DevOps, and platform engineering teams to create responsible agentic factory standards for guardrails, governance, secure releases, observability, and production readiness. 
  • Coach engineers, lead design reviews, guide implementation toward approved architecture patterns, and drive practical tradeoffs across cost, speed, reliability, and security. 
Qualifications

Required Profile 

  • 8 to 10 years of engineering experience, including 7+ years building and operating production systems on cloud platforms, plus hands-on AI/ML service deployment in production. 
  • 2-3 years using AI coding tools (Claude Code, Codex, Cursor) to automate platform buildout, deployment, testing, troubleshooting, and documentation. 
  • Strong experience with GCP/AWS or hybrid cloud/datacenter deployments; Docker, Kubernetes, GitHub Actions with reusable workflows and self-hosted runners, Terraform, and Helm. 
  • Working knowledge of authentication and authorization (OAuth 2.0, OIDC, SAML, JWT, RBAC, IAM), including workload identity, service-to-service auth, and securing API and tool access. 
  • 4+ years scripting and automation experience, preferably Python and JavaScript, with strong troubleshooting across Linux, containers, Kubernetes, networking, and production incidents. 
  • Ability to architect secure, cost-efficient hosting for open-source LLMs, on-prem or in dedicated cloud, as an alternative to commercial model APIs. 

Preferred Differentiators 

  • Agentic AI frameworks (LangGraph, Google ADK), agent-to-agent (A2A) patterns, tool calling, AI workflow orchestration, RAG, evaluation, and responsible AI guardrail design. 
  • AI-specific observability and tracing (LangSmith, Grafana/LGTM), GPU infrastructure for model serving (NVIDIA GPU Operator, Vertex AI), and DAG-based orchestration (Dagster, Prefect, Airflow). 
  • Excellent communication, mentoring, stakeholder management, and project planning, with flexibility for critical deployments and production incidents. 

Success Measures 

  • Reusable deployment patterns are documented, automated, adopted, observable, and auditable across key agentic AI workloads. 
  • Dev, UAT, and Production release paths become faster, more secure, more consistent, and easier to govern. 
  • Security, governance, reliability, monitoring, and responsible automation are embedded into delivery workflows from the start. 

 

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. #LI-REMOTE #LI-JL1

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.

 

Pay RangeUSD $105,800.00 - USD $180,200.00 /Yr.

About RealPage

RealPage is a provider of software and data analytics to the real estate industry. The company's platform enables property owners and managers to manage their properties, including leasing, accounting, and maintenance, among other services. RealPage's clients include property owners, managers, and investors. The company was founded in 1998 and is headquartered in Richardson, Texas.
Learn more about RealPage
Size
1 employees
Market Cap
$9 billion
Industry
Net Income
$46.3 million
Founded
1998
5 Year Trend
+19.8%
Revenue
$1.1 billion
NASDAQ

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