AI Platform Engineer

Advanced Systems Design is seeking an AI Platform Engineer for our client located in Montgomery, AL.

This position is onsite in Montgomery, AL, and requires in-person availability starting day 1.

The ideal candidate for this role is an early-career to mid-level engineer with strong cloud, SaaS, systems, application, automation, or platform administration fundamentals who has practical exposure to modern AI services and wants to work hands-on across multiple enterprise AI platforms.

The AI Platform Engineer is a hands-on technical position responsible for configuring, administering, integrating, operating, and supporting enterprise Artificial Intelligence (AI) platforms and related services. The position will initially work across OpenAI/ChatGPT, Microsoft Copilot, and Google Gemini capabilities, with responsibilities expanding as additional AI platforms are adopted. The engineer helps turn AI products into reliable enterprise services by supporting access, integrations, automation, monitoring, documentation, security controls, governance requirements, and day-to-day technical operations.

This is not primarily a consulting, data-science, or custom model-training role; it is an enterprise platform engineering and service-support role.

• Administer and support enterprise AI platforms, initially including OpenAI/ChatGPT, Microsoft Copilot, and Google Gemini.
• Configure platform settings, environments, tenants/work spaces, user and group access, permissions, roles, service controls, and approved feature availability.
• Assist with implementation of APIs, connectors, agents, automation, plugins/extensions, knowledge sources, and integrations between AI platforms and enterprise systems.
• Support identity and access requirements including role-based access, service identities, OAuth/OIDC or SAML-based integrations, and least-privilege access patterns as applicable.
• Troubleshoot platform, configuration, authentication, authorization, integration, data-access, performance, and service-availability issues.
• Monitor service health, utilization, licensing, consumption, logs, alerts, platform changes, and operational metrics; elevate and coordinate issues when needed.
• Assist with provisioning, modification, change, release, and retirement processes for AI services, agents, integrations, and related technical components.
• Maintain inventories of approved AI services, applications, agents, integrations, service accounts, knowledge sources, and technical dependencies.
• Implement approved security, privacy, data-protection, governance, records, and compliance requirements within supported AI platforms.
• Participate in technical reviews and testing of new AI use cases, platform features, models, agents, and service changes before broader deployment.
• Create and maintain technical documentation, configuration records, support procedures, runbooks, knowledge articles, and operational standards.
• Provide Tier 2/Tier 3 support for AI-related incidents and service requests and coordinate with vendors or internal teams for escalation.
• Develop scripts, workflows, or lightweight automation using Power Shell, Python, APIs, or comparable tools to improve repeatability and supportability.
• Work collaboratively with cybersecurity, cloud/infrastructure, identity, application, data, service-management, legal/compliance, and business teams.

• Approximately 2 - 4 years of professional experience in cloud, systems, platform, application, Dev Ops, automation, enterprise SaaS administration, technical support, or a closely related engineering discipline.
• At least one year of meaningful exposure to AI, intelligent automation, generative AI, or AI-enabled enterprise platforms; equivalent hands-on project experience may be considered.
• Hands-on experience with at least one major AI ecosystem and the ability to learn and support additional platforms.
• Working knowledge of APIs, identity/access concepts, cloud/SaaS administration, troubleshooting, change management, and technical documentation.
• Ability to work in a service-oriented environment and support both technical teams and end users while maintaining appropriate security and governance controls.
• Ability to learn rapidly changing AI platforms and evaluate the operational impact of new features and models.
• Strong troubleshooting and root-cause analysis skills across cloud services, identity, APIs, integrations, and enterprise applications.
• Ability to translate policy or control requirements…