Senior AI Platform Engineer

RealPage, Inc.

Senior Engineer at RealPage focusing on AI platform delivery, automation, and governance. Leading standards for secure deployment, incident response, and team collaboration in engineering practices.

Posted 7/21/2026full-timeRichardson • Texas • 🇺🇸 United StatesSenior💰 $105,800 - $180,200 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in defining deployment patterns for responsible AI agents and automating AI platform buildout, with a strong focus on secure architectures and incident response. Proven ability to collaborate across teams and coach engineers in implementing best practices for production readiness.

Highest-signal resume keywords

AI/ML Service DeploymentCloud Platform EngineeringTerraform and HelmAuthentication and AuthorizationScripting and Automation

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Applicant Tracking System Keywords

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Hard Skills

AI Coding ToolsProduction Systems EngineeringIncident ResponseCapacity PlanningMonitoring and ObservabilityScripting in PythonScripting in JavaScriptTroubleshootingDeployment AutomationSecure Architecture Design

Soft Skills

CoachingCollaborationLeadershipGuidance

Tools & Technologies

GCPAWSDockerKubernetesGitHub ActionsOpenTelemetryCI/CDLinuxRBACIAM

Industry Keywords

Responsible AIProduction ReadinessGovernanceGuardrailsDisaster Recovery

Tech Stack

Tools & technologies

AWSCloudDockerGoogle Cloud PlatformJavaScriptKubernetesLinuxPythonTerraform

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

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.

Benefits

Comp & perks

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.