IT - OIT - AI Platform Engineer

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. Position Summary 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.

Job Description
Title: IT - IT - OIT - AI Platform Engineer
Duration: 6 months Contract
Location: 100 N Union Street, Montgomery, AL - 100% Onsite
 
Ideal Candidate Profile:

• 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.

 
Position Summary

• 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

 
Position Description
Primary Responsibilities

• Administer and support enterprise AI platforms, initially including OpenAI/ChatGPT, Microsoft Copilot, and Google Gemini.
• Configure platform settings, environments, tenants/workspaces, 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;escalate 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 PowerShell, 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

 
Minimum Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, Cybersecurity, or a related technical discipline, or an equivalent combination of education and relevant professional experience.
• Approximately 2 - 4 years of professional experience in cloud, systems, platform, application, DevOps, 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.

 
Preferred Qualifications

• Experience with OpenAI/ChatGPT Enterprise or Business, OpenAI APIs, Microsoft Copilot/Copilot Studio/Azure AI services, or Google Gemini/Vertex AI/Google Workspace.
• Experience supporting APIs, connectors, AI agents, retrieval-augmented generation (RAG), enterprise search, knowledge grounding, or related integration patterns.
• Experience with PowerShell, Python, REST APIs, JSON, scripting, workflow automation, or low-code automation platforms.
• Experience with Microsoft Entra ID, Google identity, IAM/RBAC concepts, service principals/service accounts, secrets, permissions, or access reviews.
• Familiarity with enterprise security, privacy, data-loss prevention, records/data handling, responsible AI, and AI governance requirements.
• Experience using IT service management practices for incident, request, change, problem, knowledge, and service operations

 
Knowledge, Skills, and Abilities

• 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 into practical configuration, support, and operating procedures.
• Clear technical writing and documentation skills with an emphasis on repeatability and supportability.
• Ability to manage multiple tasks, prioritize incidents and service requests, and communicate effectively with technical and nontechnical stakeholders.