AI Engineering Lead (HYBRID - DALLAS, TX LOCAL ONLY)

Role: AI Engineering Lead

Employment type: Contract

Experience: 15 years + Experience in Data Architecture, AI and Cloud Platforms.

Job Description:

As an AI Engineering Lead, you will be the strategic glue between business goals and IT execution. You wont just be looking at individual servers or apps; youll be designing the "AI Transformation plan" for our entire digital ecosystem. Your mission is to ensure that our AI and Data technology stack is scalable, secure, andmost importantlyaligned with where the company wants to be in five years`

Key Responsibilities

• Strategic Road mapping: Develop and maintain a holistic view of the Dallas County IT organizations strategy, processes, information, and assets.
• AI Governance: Define and enforce AI standards, design patterns, Participate in Architecture Review Board management, and "golden paths" to reduce technical debt and architectural sprawl.
• Technology Lifecycle Management: Decide when to adopt emerging technology and partner with Infrastructure Operations team to coordinate efforts to sunset legacy systems.
• Cross-Functional Leadership: Bridge the gap between C-suite executives and engineering teams, translating business "asks" into technical "hows."
• AI Solutions Delivery: Review high-level designs for major AI projects to ensure they fit into the broader enterprise architecture framework. Commit to delivery of AI led Solutions managing team of AI Developers, AI Engineers and Cloud SMEs to deliver consistent AI Artifacts (Chatbots, Multi Agentic Orchestrators, LLM Optimizations, AI API Integrations, Hyperscale led AI Engineering Blueprints in AWS etc.)
• AI Projects Ownership: Review high-level designs for major IT projects and coordinate with IT Application Executive Leadership teams to deliver AI projects aligned to AI architecture principals and support PMO activities with broader teams.
• Cloud Expertise (AWS and Azure): Define and enforce Cloud standards, design Cloud patterns, Cloud Architecture and Well architected Framework review and

coordinate efforts with CSO, CPO and Data Engineering teams to set the Cloud Standards for IT Modernizations

• AI Engineering: Lead and mentor resources to deliver on AI Engineering principles including coordination with Chief Security office and Executive Leadership teams to train, educate and align on AI enterprise standards and best practices.