Artificial Intelligence ("AI") Architect

Advanced Systems Design is seeking an Artificial Intelligence ("AI") Architect for our client located in Montgomery, AL. This position is onsite in Montgomery, AL, and requires in-person availability starting day 1. Job Overview: 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. Ideal Candidate Profile: An experienced enterprise platform engineer who can work deeply in the backend while also designing the service structure around AI. The ideal candidate can engineer integrations and controls, own complex troubleshooting, operationalize governance requirements, establish standards, and mentor less-experienced AI platform resources. 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. Required Qualifications: Approximately 4 - 7+ years of professional experience in cloud engi…

View the full posting and apply