VP, AI Transformation

FlightSafety International•Columbus, OH

About The Position

The VP, AI Transformation is responsible for defining, establishing, scaling, and leading AI transformation in a complex, high-value industry environment, building and scaling enterprise-wide adoption of AI capabilities from the ground up. This role will define how AI drives competitive advantage across manufacturing, engineering, and aviation training operations, and be accountable for evolving AI from experimentation into enterprise capability, delivering measurable impact across cost structure, operational performance, and product innovation. This role requires a leader with demonstrated experience building foundational capabilities, educating stakeholders, identifying high-value opportunities, and implementing secure, compliant, and scalable AI solutions for the business. This candidate will balance innovation with risk management while ensuring compliance with defense industry requirements, cybersecurity regulations, global data protection laws, and international operational considerations.

Requirements

Bachelor's degree from an accredited institution or equivalent industry experience
Seven or more years spearheading the development and execution of AI engineering, software engineering, and/or advanced data science initiatives, with experience in designing and delivering adaptive/intelligent solutions, coordinating AI platforms, and selection/use of AI embedded in enterprise applications.
5+ years leading enterprise-scale technology transformation programs
Experience developing AI, analytics, automation, or digital transformation strategies and strong understanding of generative AI, machine learning, large language models, automation technologies, and enterprise AI platforms
Experience operating within regulated industries or government contracting environments preferred
Proven track record of driving measurable business impact at scale
Demonstrated success building and leading cross-functional transformation teams
Understands how decision intelligence, agentic AI, and other AI practices/approaches/application areas can transform decision making and work practices.
Articulate AI's transformative impact on current and future business objectives, including its potential to drive new business models, regenerate existing workflows, optimize operations, and deliver measurable value based on key performance indicators (KPIs).
Experience integrating AI into complex, legacy-rich environments.
Demonstrates the ability to comprehend industry dynamics and the organization's core mission to pinpoint where AI can yield the most significant impact and competitive advantage, while also identifying relevant business risks and opportunities, including how AI can disrupt or extend existing business models.
Pragmatic and execution-focused (avoids hype-driven approaches)
Builder mindset—comfortable creating capability from zero
High accountability and bias for results
Strong commercial acumen—can tie initiatives directly to P&L impact
Ability to operate at both the Executive/board level and Hands-on execution level
Exceptional stakeholder influence across technical and non-technical audiences
Superior analytic and decision-making skills. Ability to quickly size up where and how the organization creates value, identify opportunities and risks, and develop appropriate, actionable plans
Expert ability to develop strong business partnerships and influence senior and executive management
Expert experience managing remote/virtual teams and partners
Excellent mentoring and team development skills

Nice To Haves

Advanced degree and/or certifications in AI preferred
Preferably ten or more years in various adjacent areas. This should include, but not be limited to, software engineering, data engineering & management, analytics, AI models life cycle management, knowledge engineering, unstructured data & information management, and familiarity with a wide array of AI techniques.
Experience in manufacturing, aerospace, aviation, or engineering-intensive industries strongly preferred

Responsibilities

Define and execute a multi-year AI strategy roadmap aligned to business priorities and the modernization of digital initiatives
Build a value-backed portfolio of AI initiatives tied to cost reduction, throughput and quality improvements, and revenue enablement
Establish a roadmap which balances innovation, operational efficiency, risk management, and quantitative value
Develop a scalable AI operating model (people, process, technology, governance) and partnering with executive leadership to identify & prioritize the opportunities across all business units
Partner with finance and establish clear ROI frameworks and accountability for outcomes
Deliver material EBITDA impact through AI-driven initiatives
Stand up and scale an AI Center of Excellence (CoE)
Lead operational transformation across corporate functions, manufacturing operations, engineering and simulation by incorporating AI into core business workflows and processes building executive & leadership understanding of AI capabilities, limitations, risks and emerging trends.
Define the enterprise AI architecture in partnership with IT and executive leadership
Establish enterprise AI governance, including responsible AI principles, model risk management and data privacy and IP protection
Partner with Legal, Risk, and Cybersecurity to mitigate emerging threats
When appropriate, ensure AI initiatives align with defense industry requirements, including: CMMC (Cybersecurity Maturity Model Certification), NIST SP 800-171, NIST SP 800-53, Controlled Unclassified Information (CUI) handling requirements, Export control considerations, Government customer cybersecurity requirements
Establish secure AI usage standards for environments containing sensitive, regulated, or controlled information.
Collaborate with cybersecurity, compliance, legal, and contracts teams to evaluate AI-related risks, contractual obligations, and emerging threats.
Develop policies governing use of commercial and generative AI platforms in regulated environments
Drive enterprise-wide change management and adoption while assessing organizational and system readiness related to data quality, architecture, and governance
Guide decisions regarding AI cloud services, private environments and enterprise architectures while ensuring the initiatives align with the evolving architecture and cybersecurity standards.