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AI Platform & Services Engineer

TechNix LLCMontgomery, AL🇺🇸United StatesPosted Oct 7, 2026

Quick Overview

Seniority
Mid Senior
Work mode
On Site
Location
Montgomery, AL, United States
Posted
3 days ago
Machine LearningOAuthSAMLSSOAzureComplianceGenerative AIGoogle CloudOnboardingPowerShellProcurementPythonREST

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.

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