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

About the role

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.

Responsibilities

• 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).

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.
• 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.

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).

Pay

$205,000 to $235,000 per year.

Schedule

Hybrid model with in-person work expected 40-60% of the time over the course of an engagement, project or year.