EY-Parthenon - Strategy and Execution - Growth Platforms - AI ML Engineering - Director

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.

Within the EY-Parthenon service line, the EY Growth Platforms AI ML Engineering Director will collaborate with Business Leaders, Data Scientists, Project Managers, and other team members to design, build, and scale innovative AI solutions that power strategic growth initiatives and create enterprise value for F500 clients.

 

Your key responsibilities

 

The EY Growth Platforms AI ML Engineering Director will play a critical role building and maintaining our core advanced analytics platform and serving the technical execution lead for high-visibility client engagements. You’ll work with Business leaders and C-level executives to translate business needs into technically executable ML agentic workflows and guide a high-performing team of engineers and contractors through end-to-end project lifecycles.

 

Skills and attributes for success

• Partner with Business and Strategy Leads to translate business needs into executable AI workflows, data pipelines, and client-specific product specifications.
• Define the end-to-end architecture for agents that integrate LLMs, retrieval-augmented generation (RAG), multi-source data ingestion, and analytics components.
• Lead model selection, feature design, embedding strategy, and prompt frameworks (e.g., LangChain, LlamaIndex).
• Design and build robust data pipelines that are scalable, reproducible, and versioned.
• Collaborate with Data Engineering and DevOps on pipeline integration, data normalization, and system deployment.
• Set coding standards and mentor junior engineers; perform model/code reviews and LOE, scope and roadmap refinement.
• Own delivery of AI/ML-powered components from prototype to production (REST APIs, dashboards, or embedded agents).

 

To qualify for the role, you must have

• 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. 
• Full-time, hands-on experience applying AI/ML to solve real-world problems.
• Familiarity with multi-modal agent frameworks (LangChain, Haystack, RAG pipelines).
• Expertise in vector databases (e.g., Pinecone, Weaviate, Chroma), retrieval systems, and LLM fine-tuning.
• Strong understanding of real-world structured data merging, schema linking, and model evaluation at scale.
• Strong understanding of ML workflow including ingesting, analyzing, transforming data, and evaluating results to make meaningful predictions.
• Fluency in Python, PyTorch or TensorFlow, with ability to architect APIs around ML models.
• Proven experience designing, building, and maintaining ML models, frameworks, and pipelines.
• Experience working with and/or leading cross-functional business/engineering teams to deliver complex solutions.
• Excellent communication skills, with the ability to convey complex, technical concepts and progress, methodologies, solutioning, and results to business and client stakeholders.

• The ability and willingness to travel and work in excess of standard hours when necessary.

 

Ideally, you'll also have

• Experience building and deploying AI/ML products or feat