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TMC Acquisition LLC
AI Enablement Architect
Career Insights for Artificial Intelligence Engineer (General)
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What they do
An Artificial Intelligence Engineer develops, tests, and deploys artificial intelligence models. May work closely with data software engineers and data professionals to train and implement AI models into existing systems or develop new applications.
$141,158 / year median in Kentucky
Job Description
The AI Enablement Architect is a hands-on, cross-functional role responsible for accelerating the adoption and impact of AI across TMC. This person will operate as both a force multiplier for our staff and a technical authority on AI tooling, governance, and integration. They will work directly with operations, sales, finance, quality, and the development team to identify high-leverage opportunities, design workflows, build and deploy solutions, and train people to use AI tools well and safely. What You Will Do Enablement and Training Build and deliver AI literacy and prompting curricula tailored to each function (operations, sales, finance, quality, executive, dev). Run regular office hours, workshops, and one-on-one coaching to help staff get genuine productivity gains from Claude and other approved AI tools. Develop reusable prompt libraries, templates, and playbooks for high-frequency tasks across departments. Measure adoption and impact and report progress to the CIO and executive team. Workflow Design and Automation Identify and prioritize AI use cases across production planning, prescription operations, customer service, finance, reporting, and quality. Design and implement AI-assisted workflows using Claude, Power Automate, custom integrations, and other tooling as appropriate. Build proofs of concept quickly, validate them with operators, and iterate to production-ready solutions. Partner with operations leaders to apply AI to forecasting, capacity planning, and exception handling. Developer Productivity Lead adoption of AI coding tools (Claude Code, Cursor, GitHub Copilot, or equivalent) across the development team. Establish best practices, code review patterns, and guardrails for AI-assisted development. Coach developers on effective use of AI for code generation, refactoring, testing, documentation, and SQL work. Contribute hands-on to internal tooling, automation scripts, and integration work where it accelerates the team. Governance, Security, and Compliance Own day-to-day execution of TMC's AI Governance Policy, including tool intake, evaluation, BAA verification, and approval workflows. Ensure all AI usage is consistent with