DVP, Artificial Intelligence
AMETEK · Berwyn
The DVP, Artificial Intelligence, will be responsible for driving the adoption and implementation of AI technologies across the $2.5B Aerospace & Power Group. This role requires a leader who combines vision with execution — someone who can articulate a strategy for AI while also rolling up their sleeves to gather business requirements, experiment through proofs-of-concept and pilots, and manage projects hands-on with vendors and other stakeholders.
The DVP will set direction and actively configure solutions (including learning and applying Microsoft Copilot Studio and related platforms) to deliver tangible outcomes. Success in this role requires balancing divisional technology and architectural needs with the broader corporate architecture and long-term enterprise direction.
Key Responsibilities:
AI Strategy & Vision
- Develop and communicate a clear AI strategy aligned with divisional and enterprise goals.
- Stay current on emerging AI technologies, trends, and best practices, translating them into actionable opportunities.
- Balance visionary planning with hands-on delivery — ensuring strategy is grounded in practical execution.
Opportunity Identification & Prioritization
- Partner with divisional businesses to collect requirements and identify high-value use cases.
- Work with stakeholders to translate broad ideas into clear, actionable initiatives. Establish boundaries for what is in- and out-of-scope, clarify dependencies, and agree on success criteria upfront. Ensure alignment between divisional needs and available resources, while keeping focus on outcomes that can demonstrate early value.
- Evaluate feasibility, ROI, and alignment with corporate and divisional priorities.
- Run POCs and pilots, applying a “fail fast, pivot, and refine” approach.
- Where existing tools aren't suitable; identify and evaluate external vendors offering AI tools and platforms; assess their capabilities, scalability, and alignment with divisional needs to select the most effective solution for each initiative.
Project Leadership
- Lead end-to-end implementation of AI projects, from proof-of-concept to production deployment.
- Work directly with vendors and internal teams to ensure timely, effective delivery.
- Learn and configure AI platforms (e.g., Microsoft Copilot Studio) to demonstrate and scale use cases.
- Ensure projects integrate seamlessly with both divisional and corporate architectures.
Governance & Compliance
- Act as a key liaison between divisional IT and corporate IT.
- Surface technology gaps, navigate approval processes, and maintain compliance with enterprise standards.
- Ensure divisional solutions leverage and align with corporate platforms, tools, and architecture direction.
- Work with security, data privacy, and compliance teams to ensure all AI initiatives meet regulatory and corporate requirements.
- Document lessons learned and help refine enterprise AI governance frameworks.
- Review software/tool licenses and vendor contracts in collaboration with legal teams to execute agreements.
Stakeholder Engagement
- Serve as a trusted advisor to divisional leadership and business units, bridging strategy with execution.
- Communicate AI vision, progress, and business impact to stakeholders at all levels.
- Build trust by showing both thought leadership and hands-on results.
Qualifications:
- Proven experience delivering AI initiatives in an enterprise environment, with a balance of strategic and hands-on execution.
- Strong understanding of AI platforms, tools, and use cases; willingness to learn and configure solutions directly.
- Ability to translate business problems into working AI prototypes and production solutions.
- Experience liaising across divisional and corporate IT functions, with knowledge of governance and compliance processes.
- Excellent project management, vendor management, and stakeholder engagement skills.
- Experience with cloud platforms, data engineering, and MLOps is a plus.
- Demonstrated ability and willingness to use AI tools to improve productivity, decision-making, work quality, and to reduce costs. The successful candidate must be able to identify appropriate AI use cases and critically evaluate AI-generated outputs.
Preferred Background:
- Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related field.
- 10+ years of technology leadership experience, with at least 3 years focused on AI initiatives, or equivalent experience.
- Experience in regulated industries (e.g. Aerospace)
- Track record of successfully running pilots/POCs and scaling them into production.