Kyle Steelman

Director of Ai Engineering @Aetna, A Cvs Health Company

Middletown, DE, US
MOBILE NUMBERS
+13•••••••15

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WORK HISTORY

Jul 2025 — Present

Director of Ai Engineering @Aetna, A Cvs Health Company

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Director of AI Engineering building a high-impact, senior team to scale AI across the enterprise- Leading the design of foundational systems, org structure, and practices for a modern Enterprise AI organization- Hiring AI Product & Systems Engineers to deliver production-grade LLM features using off-the-shelf models and RAG- Driving full-stack AI delivery: prompt design, evaluation, infra, and model integration at scale- Focused on trust and measurable impact through AI-powered workflows in real business contexts

EDUCATION

2006 — 2010

University of Delaware

BE, Mechanical Engineering

2013 — 2016

University of Delaware

Master of Business Administration (MBA), Business Administration and Management, General

SKILLS

Project ManagementSolidworksLean ManufacturingCResource ManagementGitStatistical ModelingManufacturing EngineeringPro EngineerManufacturingHoneycomb ManufacturingObjective-CHtmlIphone Application DevelopmentCssStatistical Data AnalysisCompositesProcess ImprovementJavascriptSwiftAutocadRProcess Design

ABOUT KYLE STEELMAN

I’m currently Director of Mobile Engineering at Aetna, where I lead teams building and scaling mobile experiences within a large-scale, regulated healthcare environment.Since early 2025, my focus has shifted toward AI enablement within engineering organizations. My core priority is training engineers in applied AI—covering topics such as LLM integration, agent workflows, and prompt engineering—to ensure teams are equipped to adapt and thrive as AI becomes central to modern software development.My approach is grounded in delivery: leverage AI where it creates measurable value, build maintainable systems, and drive long-term capability across teams. Core Responsibilities- Leading mobile engineering strategy and delivery across Aetna’s consumer platforms- Aligning AI tooling with product and platform roadmaps- 🧠 Training engineers in GenAI, prompt design, and automation workflows- Building processes to integrate AI into development and decision-making at scale GoalsTo build engineering teams that are technically excellent, AI-aware, and structurally prepared for the next generation of software development.

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