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

EY•Atlanta, GA

7d•$205,000 - $235,000•Hybrid

About The Position

EY-Parthenon's unique combination of transformative strategy, transactions, and corporate finance delivers real-world value. Benefiting from EY’s full spectrum of services, we’ve reimagined strategic consulting for a complex world. With deep functional and sector expertise, innovative AI-powered technology, and an investor mindset, we partner with CEOs, Boards, Private Equity, and Governments to shape the 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 trustworthy, explainable, and 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 measurable business outcomes.

Requirements

A bachelor’s degree in Business, Statistics, Economics, Mathematics, Engineering, Computer Science, Analytics, or other related field and 5 years of related work experience; or a graduate degree and approximately 3 years of related work experience.
7+ years in product leadership, solution delivery, enterprise technology, or platform build roles.
Proven experience building and launching enterprise-grade products.
The ability and willingness to travel and work in excess of standard hours when necessary.
Must either reside in or be in a commutable distance to your office location for this position.
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 in ambiguous, complex environments.
Executive communication skills with the ability to influence senior stakeholders.
Experience defining product strategy, roadmaps, and success metrics.

Nice To Haves

Experience with neuro-symbolic AI frameworks, knowledge representation, or semantic data platforms.
Background working with regulated industries (Financial Services, Health, Government, Energy, etc.).
Experience with large-scale cloud architectures (Azure, AWS, GCP) and enterprise data platforms.
Prior leadership in building reusable AI platforms or multi-tenant enterprise solutions.
Knowledge of how to leverage AI tools in a business setting, including Microsoft Copilot.

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.