AI Platform Engineer

AI Platform Engineer

Location: Montgomery, AL

Onsite Flexibility: Onsite

Contract Details

• Position Type: Contract
• Contract Duration: 1 year (contract-to-hire — conversion to Merit position pending confirmation of candidate eligibility)
• Pay Rate: $40.00–$47.00 / Hour (USD)
• Work Authorization: Applicants must be authorized to work for ANY employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.

Job Summary

This opportunity is designed for anearly-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 acrossOpenAI/ChatGPT,Microsoft Copilot, andGoogle 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 Snapshot:

• Primary Function: Hands-on AI platform engineering, administration, integration, operations, and Tier 2/Tier 3 support.
• Initial Platforms: OpenAI/ChatGPT, Microsoft Copilot, and Google Gemini; additional enterprise AI services as adopted.
• Service Focus: Provisioning, access, configuration, connectors/APIs, automation, monitoring, troubleshooting, documentation, and lifecycle support.
• Governance Role: Implements approved governance, security, privacy, compliance, and data-handling controls in platform configurations and operating procedures.
• Candidate Background: Cloud engineering, systems/platform engineering, enterprise SaaS administration, application support, DevOps/automation, IAM/security, or related technical disciplines.
• Consulting Background: Not required. Demonstrated hands-on technical ownership and operational support are more important than advisory experience.

Key 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.

Required Skills

• 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 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.

Capability Chart — Expected Levels:

• OpenAI / ChatGPT: Working knowledge — administrative, API, workspace, access, or enterprise-use experience; ability to support OpenAI-based services.
• Microsoft Copilot: Working knowledge — exposure to Microsoft 365 Copilot, Copilot Studio, Azure AI services, Power Platform, or related administration.
• Google Gemini: Working knowledge — exposure to Gemini, Vertex AI, Google Cloud, or Google Workspace AI capabilities; transferable experience acceptable.
• Cloud / SaaS Administration: Working — configuration, access, tenant/workspace administration, licensing, monitoring, service changes, and troubleshooting.
• APIs / Integrations: Basic–Intermediate — REST APIs, connectors, JSON, authentication, service endpoints, integration troubleshooting, or workflow integration.
• Automation / Scripting: Basic–Intermediate — PowerShell, Python, workflow tools, or similar automation used to improve support and repeatable operations.
• AI Agents / RAG: Exposure–Working — basic understanding of agents, tools, knowledge sources, grounding, retrieval, and enterprise data-access considerations.
• Identity & Access: Working — RBAC, groups, service identities, SSO concepts, access reviews, least privilege, and permission troubleshooting.
• Security / Privacy / Governance: Working — ability to implement approved controls, document configurations, support reviews, and maintain evidence as required.
• IT Service Management: Working — incident, request, change, problem, knowledge, escalation, runbooks, and operational support processes.

Preferred Skills

• 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.

Education Requirements

• 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.

Required 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.

Benefits

• Medical, Vision, and Dental Insurance Plans
• 401k Retirement Fund

Important Notes

• Candidate will work 100% onsite in Montgomery, AL. No remote work allowed.
• Background check: ALEA check required.
• Interview format: Virtual or onsite based on location.
• This role offers a contract-to-hire pathway; confirmation is needed to verify candidate eligibility for conversion to a Merit position.

About GTT

GTT is a minority-owned staffing firm and a subsidiary of Chenega Corporation, a Native American-owned company in Alaska. We highly value diverse and inclusive workplaces and support Fortune 500 organizations across banking, financial services, technology, life sciences, biotech, utilities, and retail sectors throughout the U.S. and Canada.

Job Number: 26-15474Industry: Engineering

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