EY-Parthenon - Strategy and Execution - Growth Platforms - AI Business Build - Director

Location: New York

Other locations: Anywhere in Region

Salary: Competitive

Date: Aug 18, 2026

Job description

Requisition ID: 1730836

Location: New York, Atlanta, Boston, Chicago, Dallas, Denver, Detroit, Houston, Los Angeles, McLean, Hoboken, Philadelphia, San Francisco, Seattle

At EY, we’re all in to shape your future with confidence.

We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world.

The opportunity

EY-Parthenon’s unique combination of transformative strategy, transactions and corporate finance delivers real-world value – solutions that work in practice, not just on paper. Benefiting from EY’s full spectrum of services, we’ve reimagined strategic consulting to work in a world of increasing complexity.

With deep functional and sector expertise, paired with innovative AI-powered technology and an investor mindset, we partner with CEOs, Boards, Private Equity and Governments every step of the way – enabling you to shape your future with confidence.

The EY Growth Platform (EYGP) integrates business strategy, advanced technology, and applied AI engineering to deliver scalable AI products and platforms for the world’s largest organizations. We specialize in neuro‑symbolic AI, combining machine learning with knowledge graphs, ontologies, rules-based systems, and enterprise data assets to produce highly trustworthy, explainable, auditable AI solutions.

EYGP works across industries to build AI-powered systems that improve decision-making, automate complex workflows, and unlock new capabilities with enterprise-grade governance, Responsible AI, and real business measurable outcomes.

Your key responsibilities

Lead the build and scaling of neuro‑symbolic AI products

• Drive the full lifecycle of AI product development: problem framing, requirements, architecture, build, deployment, and scale.
• Translate complex business challenges into knowledge-driven AI product requirements, including reasoning engines, knowledge graphs, rules, and machine learning components.
• Ensure products and platforms adhere to enterprise standards for explainability, auditability, trust, and compliance.

Define product strategy, roadmap, and commercial outcomes

• Develop a clear product vision and roadmap aligned to customer needs, economic impact, and technical feasibility.
• Define adoption, usage, and cost/value metrics that demonstrate measurable business outcomes.
• Shape pricing, packaging, and commercialization pathways for AI platforms and solutions.

Architect enterprise-ready platforms using neuro‑symbolic AI

• Guide the design of platform components including ontologies, semantic data layers, inference engines, ML integration, APIs, workflow orchestration, and user interfaces.
• Ensure platform scalability, modularity, and extensibility across multiple use cases.
• Lead decisions on architecture, tooling, integration patterns, and data pipelines.

Direct cross-functional product and technical teams

• Lead teams across product management, engineering, knowledge engineering, design, data science/ML, and industry specialists.
• Establish OKRs, sprint structures, and delivery governance to ensure predictable, high-quality execution.
• Coach teams to operate with clarity, pace, and technical rigor.

Partner with senior executives and enterprise stakeholders

• Serve as a trusted advisor to client executives and internal leaders on AI strategy, product direction, and deployment models.
• Align product build with enterprise architecture, security, data governance, and compliance requirements.
• Support investment decisions with clear business cases, milestones, and measurable value.

Ensure Responsible AI and regulatory compliance

• Embed Responsible AI principles—including transparency, fairness, bias mitigation, and auditability—into product design.
• Partner with risk, legal, compliance, and cybersecurity to ensure the product meets all regulatory and policy requirements.
• Lead teams in documenting reasoning processes, knowledge sources, and decision pathways.

Skills and attributes for success

• Strong understanding of:
  • Knowledge graphs and ontologies
  • Symbolic reasoning / rules engines
  • Machine learning integration patterns
  • Data modeling, lineage, and governance
• Demonstrated ability to lead cross-functional teams …