Vice President, Enterprise Architecture & Engineering Services

BrightSpring Health Services•Lyndon, KY

About The Position

We are seeking a senior technology leader to serve as Vice President of Enterprise Architecture and Engineering Shared Services, accountable for defining and governing the enterprise’s technology direction, architectural integrity, and shared engineering capabilities. This role sits at the intersection of Enterprise Architecture (EA) and Engineering Shared Services, ensuring that technology decisions, platforms, and automation capabilities are standardized, scalable, secure, and aligned to business strategy across the enterprise. The VP will own enterprise-wide patterns, standards, best practices, frameworks, and technology selection under Enterprise Architecture, while also leading shared engineering capabilities including Enterprise RPA, Agentic AI platforms, DevOps, and Intelligent Automation. The role partners closely with product, clinical, operations, security, and data leaders to enable rapid innovation without compromising governance, compliance, or sustainability. Enterprise Architecture Enterprise patterns, standards, and reference architectures AI Center of Excellence (AI CoE) Technology selection, rationalization, and lifecycle governance Architecture frameworks, design authorities, and guardrails Interoperability, scalability, resilience, and compliance alignment Engineering Shared Services Enterprise RPA and workflow automation platforms Agentic AI and Generative AI enablement platforms DevOps, CI/CD, DevSecOps, and MLOps shared services Intelligent Automation frameworks and reusable capabilities

Requirements

15+ years of experience in enterprise architecture, platform engineering, or large scale technology leadership within healthcare or regulated industries.
Proven experience defining enterprise architecture standards, patterns, and technology governance at scale.
Strong background in automation technologies, including RPA, workflow orchestration, and intelligent automation.
Deep familiarity with Generative AI, Agentic AI, AI platform architecture, and MLOps.
Hands on experience with cloud native architectures (Azure preferred), enterprise data platforms (e.g., Databricks), and integration frameworks.
Strong understanding of healthcare interoperability standards and regulatory compliance.
Executive level communication and stakeholder management skills with the ability to influence without direct ownership of product teams.
Track record of balancing innovation velocity with architectural discipline and risk management.

Nice To Haves

Experience establishing enterprise AI or automation centers of excellence.
Thought leadership, speaking, or published work in enterprise architecture or healthcare technology.

Responsibilities

Define and maintain enterprise architecture standards, patterns, and reference architectures across application, data, integration, AI, and automation domains.
Establish and lead the Enterprise AI Center of Excellence (AI CoE), responsible for: Enterprise AI and Agentic AI standards, patterns, and guardrails
Approved AI frameworks, platforms, and model usage policies
Responsible AI, security, compliance, and risk alignment (HIPAA, PHI handling, model governance)
Reusable AI capabilities, accelerators, and reference implementations
Establish and govern technology selection and lifecycle management, ensuring alignment with enterprise strategy, security, and compliance requirements.
Lead architectural governance forums (e.g., design authorities, architecture review boards) to ensure consistency and reduce technical debt.
Ensure enterprise platforms and solutions adhere to healthcare interoperability and regulatory standards (FHIR, HL7, HIPAA).
Lead enterprise shared services for RPA, Agentic AI, DevOps, and Intelligent Automation as reusable, productized capabilities.
Oversee the design and evolution of enterprise automation platforms, enabling scalable automation across clinical, pharmacy, revenue cycle, and corporate functions.
Establish DevOps, DevSecOps, and MLOps standards that accelerate delivery while maintaining security and operational excellence.
Enable responsible adoption of Generative AI and Agentic AI, including orchestration frameworks, model integration patterns, and guardrails.
Partner with product, engineering, security, data, and business leaders to align architecture and shared services with enterprise priorities.
Define metrics and KPIs to measure architectural health, platform adoption, automation impact, and engineering productivity.
Manage budgets, vendors, and strategic technology investments across EA and shared engineering services.
Build and mentor high‑performing architecture and platform engineering leaders and teams.
Drive enterprise training and enablement on architecture standards, automation platforms, and modern engineering practices.