Data Mod & Applied AI Lead

Opportunity: Data Mod & Applied AI Lead Salary Range: $140,000 - $200,000 Division: Digital Services Job Posting End Date: Work Designation. Depending on your location within the continental US, this role may be hybrid or remote. • If you live within 50 miles of the Aflac offices located in Columbus, GA or Columbia, SC, this role will be hybrid. This means you will be expected to work in the office for at least 60% of the work week. You will work from your home (within the continental US) for the remaining portion of the work week. Details of this schedule will be discussed with your leadership. • If you live more than 50 miles from the Aflac offices located in Columbus, GA or Columbia, SC, this role will be remote. This means you will be expected to work from your home, within the continental US. If the role is remote, there may be occasions that you are requested to come to the office based on business need. Any requests to come to the office would be communicated with you in advance. What does it take to be successful at Aflac? • Acting with Integrity • Communicating Effectively • Pursuing Self-Development • Serving Customers • Supporting Change • Supporting Organizational Goals • Working with Diverse Populations Overview : Lead the data and applied AI program that modernizes our data foundation and builds new data products and agentic processes for the business. The program includes migrating legacy batch ETL to a cloud-native medallion architecture across insurance domains, replacing legacy BI tools with a serverless self-service analytics platform, and deploying AI agents across the data landscape. Delivery is tracked through git repositories rather than Scrum or SAFe ceremonies or a ticketing system. This is not a hands-on engineering role, but it requires daily work in git, markdown, and AI development tools. What does it take to be successful in this role? • Experience with cloud data platforms (AWS, Azure, or GCP data services stack) • Familiarity with medallion architecture / modern data platform patterns • Experience with spec-driven AI development environments (Kiro, Claude Code, or similar) • Background in insurance, financial services, or other regulated industries • Experience managing programs where AI agents perform significant portions of the implementation work • Interest in or exposure to applied AI — agentic systems, conversational interfaces, or AI-driven automation beyond developer tooling Education & Experience Required • Bachelor's Degree in Computer Science, Data Analytics, Business Administration or other related field • 6+ years leading or managing technology programs (delivery manager, technical PM, engineering manager, or similar) • Demonstrated experience with data platforms, data engineering, or analytics/BI programs • Experience with AI coding/productivity tools • Experience working in or adjacent to git-based development workflows • Track record of delivering complex programs with small, high-autonomy teams Or an equivalent combination of education and experience Education & Experience Preferred • Experience leading data platform, data engineering, or analytics/BI programs, including teams building pipelines, data warehouses, or reporting systems. • Hands-on use of AI coding tools (e.g., Kiro, Claude Code, Cursor, GitHub Copilot) in own work, not only managing teams that use them. • Working proficiency with git, pull requests, and markdown-based documentation. Principal Duties & Responsibilities • Lead AI-enabled requirements management by leveraging AI tools and agents to develop comprehensive intent-based specifications that clearly define business objectives, acceptance criteria, solution requirements, and design constraints, enabling consistent and unambiguous execution. • Own and evolve the program knowledge ecosystem, maintaining a structured repository of architecture documentation, decision records, roadmaps, standards, and domain knowledge that serves as the authoritative source for both human teams and AI-enabled workflows. • Drive data-informed program execution by leveraging repository-based metrics and delivery signals to monitor specification progress, workflow health, cycle times, and program outcomes, eliminating reliance on manual status reporting. • Manage and prioritize the delivery portfolio, evaluating business value, dependencies, risks, and resource capacity to sequence work effectively and decompose complex initiatives into actionable, executable workstreams with AI-assisted analysis. • Ensure solution quality and value realization by validating delivered capabilities against defined acceptance criteria, assessing outcomes, and identifying opportunities to improve requirements, processes, or execution approaches. • Continuously enhance delivery standards and governance frameworks by establishing and maintaining reusable patterns, guidance, and operational controls that improve consistency, quality, and scalability across AI-enabled development efforts. • Translate technical progress into business outcomes, providing stakeholders with clear insights through meaningful metrics, demonstrations, and value-focused communications that drive alignment and decision-making. • Guide strategic trade-off decisions across speed, quality, cost, risk, and automation considerations to optimize program outcomes while balancing short-term delivery needs with long-term sustainability. • Define and measure program success, establishing key performance indicators, success metrics, and value realization frameworks that drive accountability and continuously improve delivery effectiveness, specification quality, and operational efficiency. • Champion AI-driven ways of working by embedding AI capabilities into program management, delivery processes, and decision-making practices to accelerate innovation, improve productivity, and enhance organizational effectiveness. • Performs other duties as required Tota