AI Platform & Services Engineer

Technix LLC; Montgomery (AL); On-site; USD 120,000 - 170,000; Full time

Job summary

Technix LLC is seeking a Senior AI Platform & Services Engineer for a 12-month engagement with the State of Alabama via OIT. Location is Montgomery, AL, with on-site work required.

The role centers on engineering, administering, and improving enterprise AI platforms, initially around OpenAI/ChatGPT, Microsoft Copilot, and Google Gemini, while establishing governance, security, and operational standards. The engineer will remain hands-on, provide technical leadership, implement integration

Qualifications

• Bachelor's degree in Computer Science or related technical field or equivalent work experience.
• 4-7+ years in cloud engineering, DevOps, or platform engineering.
• 2+ years in AI or related enterprise technologies preferred; equivalent hands-on delivery considered.
• Experience with enterprise cloud/SaaS platforms, APIs, and access controls.
• Strong troubleshooting and cross-team coordination abilities.

Responsibilities

• Engineer, administer, and improve enterprise AI platforms at scale.
• Lead hands-on technical work across OpenAI ChatGPT, Copilot, Gemini, and related tech.
• Design patterns for APIs, connectors, agents, RAG, and integrations with enterprise systems.
• Establish platform governance, access-control, and lifecycle management standards.
• Implement identity patterns, SSO, RBAC, secrets, and least privilege controls.
• Translate governance and compliance requirements into technical configurations.
• Monitor logging, costs, licensing, and performance; provide incident resolution.
• Mentor AI Platform Engineers and collaborate with security and cloud teams.

Skills

Cloud engineering

DevOps

AI platforms

Security engineering

Technical leadership

Education

Bachelor's degree in Computer Science or related field

Equivalent education + experience

Tools

OpenAI APIs

Microsoft Copilot

Google Gemini

PowerShell

Python

REST APIs

Job description

Position: Sr. AI Platform and Services Engineer

Duration: 12 Months

Agency: OIT

Job ID: 13759

Client: State of Alabama

Location: Montgomery, AL

Work Mode: Onsite

Interview Type: Virtual or onsite based on location

Position Summary

The Senior AI Platform & Services Engineer is a senior hands-on technical position responsible for engineering, administering, integrating, operating, and continuously improving enterprise AI platforms and services. The position provides technical leadership across a multi-platform AI environment initially centered on OpenAI/ChatGPT, Microsoft Copilot, and Google Gemini. The engineer establishes repeatable technical patterns, operational standards, integrations, access controls, monitoring, service-management processes, and governance implementation so AI capabilities can be operated securely and reliably as managed enterprise services. This role is expected to remain hands-on and is not primarily a consulting, policy-only, or custom model-research position.

Primary Responsibilities

• Engineer, administer, and continuously improve enterprise AI platforms and the supporting technical services required to operate them at scale.
• Serve as a hands-on technical subject-matter resource across OpenAI/ChatGPT, Microsoft Copilot, Google Gemini, and related enterprise AI technologies.
• Design and implement technical patterns for APIs, connectors, agents, orchestration, knowledge sources, retrieval augmented generation (RAG), automation, and integrations with enterprise systems.
• Establish platform administration, environment management, access-control, configuration, service onboarding, change/release, and lifecycle-management standards.
• Design and implement identity patterns including SSO, RBAC, privileged access, service identities, scopes/permissions, access reviews, secrets, and least-privilege controls as applicable.
• Translate approved governance, security, privacy, legal, compliance, records, and data-management requirements into enforceable technical configurations and operating controls.
• Evaluate data flows, model/provider interactions, knowledge sources, connectors, and integrations to identify technical risks, dependencies, logging requirements, and control points.
• Establish monitoring, logging, alerting, auditability, usage reporting, cost/consumption visibility, licensing oversight, and operational performance metrics for AI services.
• Own or lead troubleshooting of complex platform, integration, authentication, authorization, data-access, agent, performance, and service-availability issues.
• Evaluate new AI products, models, platform capabilities, agents, and features and define technical testing, pilot, release, and support-readiness requirements.
• Develop and maintain technical architecture documentation, standards, configuration baselines, runbooks, support models, knowledge articles, and operational procedures.
• Define escalation paths and support boundaries for AI-related incidents and service requests and coordinate with vendors and internal technical teams as needed.
• Identify and implement automation opportunities that reduce manual administration and improve consistency, reliability, observability, and governance.
• Provide technical mentoring and guidance to AI Platform Engineers and other support resources while maintaining hands-on ownership of critical engineering work.
• Partner with cybersecurity, cloud/infrastructure, identity, application, data, architecture, service-management, procurement, legal/compliance, and business teams on AI service delivery.

Minimum Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, Cybersecurity, or a related technical discipline, or an equivalent combination of education and progressively responsible professional experience.
• Approximately 4 - 7+ years of professional experience in cloud engineering, systems engineering, platform engineering, DevOps, enterprise application administration, automation, security engineering, or comparable technical disciplines.
• Approximately 2+ years of meaningful experience with AI, intelligent automation, machine learning platforms, generative AI, or closely related enterprise technologies is preferred; equivalent depth demonstrated through hands-on delivery may be considered.
• Demonstrated experience engineering or operating complex enterprise cloud/SaaS platforms, integrations, identity controls, APIs, and support processes.
• Strong troubleshooting capability and experience leading technical resolution of multi-system issues involving applications, cloud services, identity, permissions, APIs, or data access.
• Ability to translate architectural, security, privacy, governance, or compliance requirements into practical technical designs and operational controls.

Preferred Qualifications

• Hands-on experience with at least two of the following ecosystems: OpenAI/ChatGPT and OpenAI APIs; Microsoft Copilot/Copilot Studio/Azure AI services; Google Gemini/Vertex AI/Google Cloud.
• Experience implementing enterprise AI agents, RAG/grounding, knowledge integration, enterprise search, tool/function calling, model routing, or API orchestration patterns.
• Experience with PowerShell, Python, REST APIs, JSON, CI/CD or infrastructure automation, low-code workflow tools, or comparable automation technologies.
• Experience with enterprise IAM, Microsoft Entra ID or comparable identity platforms, OAuth/OIDC/SAML, RBAC, privileged access, service principals/service accounts, secrets, and access reviews.
• Experience implementing security, privacy, data-loss prevention, logging/audit, records/data-handling, responsible AI, or AI governance requirements in technology platforms.
• Experience establishing IT service-management models including incident, request, change, problem, knowledge, service ownership, escalation, monitoring, and operational reporting.
• Experience operating technology in a regulated, government, large-enterprise, or other control-intensive environment.

Knowledge, Skills, And Abilities

• Strong systems-thinking skills and the ability to understand how AI platforms interact with identity, data, applications, networks, cloud services, security controls, and operational processes.
• Ability to design practical service structures around rapidly changing technology without overengineering or losing operational supportability.
• Ability to evaluate tradeoffs across platform capability, security, privacy, cost, user experience, maintainability, and compliance requirements.
• Strong technical documentation, standards development, and communication skills for both engineering and governance audiences.
• Ability to mentor engineers, provide technical direction, coordinate across teams, and maintain ownership through implementation and steady-state operations.