VP, AI & Products

AI Strategy, Productization & Engineering Transformation

The VP, AI & Intelligent Products owns the definition, development, and scaling of artificial intelligence across Automated Financial Systems (AFS). This role is responsible for establishing AI as a core driver of product differentiation, engineering velocity, and enterprise value creation.

As AFS’s first dedicated AI leader, this role is accountable for building the AI capability from first principles while simultaneously delivering near‑term product and productivity impact. The role combines strategic leadership, hands‑on technical execution, and cross‑functional influence to embed AI deeply into the company’s product and engineering operating model.

The VP, AI & Intelligent Products is a member of the Management Committee and partners directly with the CEO and peers across Product, Engineering, Revenue, Operations, and Business Intelligence. The role operates as the enterprise owner of AI strategy, execution, and outcomes, ensuring alignment between AI initiatives and overall company value creation.

The VP, AI & Intelligent Products owns the end‑to‑end AI function across AFS, including strategy, product integration, architecture, governance, and engineering enablement.

The role is empowered to define priorities, design systems, and recommend or select platforms, vendors, tools, and processes—while operating within AFS’s SOC/ISO/audit control environment. The VP partners closely with Risk and Compliance to ensure AI initiatives and operational decisions maintain fidelity to regulatory expectations, internal control requirements, and established governance programs.

The role is accountable for both building the initial AI capability directly and defining the structure, talent, and operating model required to scale the function over time.

Define and own AFS’s AI strategy and translate it into a prioritized roadmap aligned to enterprise value creation.

Deliver AI‑enabled product capabilities that create measurable customer value and differentiation.

Establish the company’s AI architecture, including LLM integration, RAG systems, agent frameworks, and MCP patterns.

Design and implement AI governance, risk management, and compliance frameworks aligned to FFIEC, SOC 2, and internal standards.

Embed AI into the engineering lifecycle to improve development velocity, quality, and efficiency.

Lead hands‑on design and implementation of initial AI systems and features.

Upskill engineering teams and drive adoption of AI tooling, workflows, and best practices.

Define and track metrics tied to engineering productivity, product impact, and AI‑enabled value creation.

Serve as the primary advisor on AI to the CEO, Executive Leadership Team, and Board.

Define and build the future AI team, including hiring strategy and organizational design.

Establish AI as a core capability embedded across AFS product and engineering workflows.

Deliver initial AI‑enabled product features into production with measurable customer impact.

Drive meaningful improvement in engineering productivity and time‑to‑delivered‑value.

Define and operationalize a scalable AI architecture and governance model.

Build a foundation for a dedicated AI organization that can scale with company growth.

Success in the first year is defined by measurable improvements in delivery speed, cost-to-serve, product differentiation, and operational rigor—while remaining compliant with AFS’s SOC/ISO/audit expectations.

• Reduce external services spend by 30% through internal capability build, platform rationalization, and automation.
• Improve time-to-delivered-value by 50% for targeted product/engineering work streams (measured from intake to production release).
• Deliver 2–4 AI‑enabled product capabilities into production with defined adoption and customer outcome metrics.
• Stand up an AI architecture and delivery foundation (e.g., RAG/agent patterns, evaluation harnesses, and reusable components) adopted by 3+ product or engineering teams.
• Implement AI governance and…