Sr. Data and AI Architect; Hybrid

At Globe Life, we are committed to empowering our employees with the support and opportunities they need to succeed at every stage of their career. We take pride in fostering a caring and innovative culture that enables us to collectively grow and overcome challenges in a connected, collaborative, and mutually respectful environment that calls us to help Make Tomorrow Better.

Could you be our next Sr. Data and AI Architect? Globe Life is looking for a Sr. Data and AI Architect to join the team! In this role, you will be responsible for designing and implementing enterprise-wide data and AI solutions that enable AI-led transformation across the organization. This role bridges traditional data architecture with modern AI engineering — driving adoption of large language models (LLMs), generative AI, agentic AI, multi‑agent orchestration, Model Context Protocol (MCP), retrieval‑augmented generation (RAG), and AI‑integrated front‑end chatbots — while identifying and delivering high‑impact use cases that accelerate enterprise AI adoption.

This is a hybrid position located in McKinney, TX. (WFH Monday & Friday, In Office Tuesday–Thursday).

• Design and oversee enterprise‑critical data and AI architecture solutions, ensuring scalability, security, data integrity, and optimal performance across cloud and on‑premises platforms.
• Lead the strategy and architecture for AI platforms, including LLM integrations, agentic AI, multi‑agent orchestration frameworks, Model Context Protocol (MCP) implementations, retrieval‑augmented generation (RAG) pipelines, vector databases, and other generative AI solutions.
• Architect and oversee agentic AI, including autonomous agent design, tool‑use patterns, agent memory management, and human‑in‑the‑loop controls for enterprise‑grade reliability and governance.
• Design and implement MCP‑based integrations to enable structured, context‑aware communication between AI agents and enterprise data sources, APIs, and services.
• Architect end‑to‑end AI‑enabled systems, collaborating with data engineers and front‑end developers to deliver production‑ready intelligent systems.
• Design and maintain enterprise data models (conceptual, logical, and physical) that serve as the foundation for AI‑powered applications, database design, and data integration efforts.
• Provide thought leadership on generative AI, agentic AI, and emerging AI protocol trends (e.g., MCP, A2A) and their applicability to enterprise business problems, particularly within the life insurance domain.
• Evaluate and implement cloud‑native AI services (AWS Bedrock, Amazon Q, or equivalent) and establish best practices for responsible AI, AI governance, and explainability.
• Communicate complex AI and data architecture concepts to diverse stakeholders at all organizational levels, including executive leadership.
• Evaluate and resolve complex data architecture challenges requiring analysis of data quality issues, SQL optimization, ETL pipeline design, and conceptual/logical/physical data modeling to understand enterprise‑wide implications.
• Influence and establish data architecture best practices across the organization, focusing on cloud data services, modern data stack technologies, and scalable data integration patterns.
• Architect and oversee ETL/ELT workflows, data pipelines, and integration processes to ensure efficient data movement and transformation across cloud and on‑premises data platforms.
• Contribute to and oversee front‑end solution design using .NET (C#, ASP.NET Core, Web API) and Angular, ensuring seamless integration between AI/data back‑end services and user‑facing AI Chatbot.
• Partner with portfolio leaders to understand analytical and AI requirements into scalable technical solutions and actionable insights.
• Establish and enforce data and AI architecture standards, governance frameworks, and best practices, including agentic AI safety guardrails, across the organization.
• Mentor and guide data engineers, AI engineers, and front‑end developers, providing technical leadership and knowledge transfer.
• Direct data and AI architecture activities to ensure successful delivery of critical enterprise…