AI Platform Engineer (Hybrid)

Smart IMS•Austin, TX

8d•Hybrid

About The Position

As an AI Platform Engineer, you will lead the deployment, administration, and optimization of enterprise AI platforms and services. This role focuses on enabling scalable AI capabilities, automating platform operations, managing integrations, and ensuring secure, reliable, and efficient adoption of AI technologies across the organization.

Requirements

Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field.
8+ years of experience supporting enterprise technology platforms, SaaS products, or large-scale enterprise applications.
3+ years of experience implementing, administering, or supporting AI, cloud, or collaboration platforms.
Proven experience deploying enterprise SaaS solutions at scale.
Strong scripting and automation expertise using Python, PowerShell, or similar technologies.
Experience building data pipelines and working with APIs, databases, cloud services, and enterprise systems.
Strong knowledge of Identity and Access Management (IAM), Single Sign-On (SSO), Entra ID/Azure AD, SAML, OAuth, OpenID Connect, and RBAC.
Experience with enterprise security controls, production support, incident management, and operational processes.
Hands-on experience with monitoring and observability tools such as Splunk, Grafana, or similar platforms.

Nice To Haves

Experience with enterprise AI platforms such as OpenAI Enterprise, Anthropic Enterprise, GitHub Copilot Enterprise, Microsoft Copilot, Azure AI Foundry, and knowledge of AI governance and compliance concepts is highly preferred.

Responsibilities

Lead the deployment and implementation of enterprise AI platforms and services.
Administer and support AI platforms, ensuring availability, performance, and operational excellence.
Monitor platform health, usage trends, and service performance while managing incidents and escalations.
Develop automation scripts and workflows to streamline platform operations and infrastructure management.
Design and maintain data extraction, transformation, and integration processes from enterprise systems and cloud platforms.
Manage platform lifecycle activities including upgrades, feature enablement, and decommissioning.
Define operational processes, service level objectives (SLOs), and support models.
Create runbooks, technical documentation, knowledge articles, and operational procedures.
Deliver user onboarding, training, and adoption programs for AI technologies.
Collaborate with vendors, security teams, and stakeholders to ensure secure and effective platform utilization.