EY-Parthenon - Strategy and Execution - Growth Platforms - Software 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

• Architect, build, and scale core software platforms that integrate data, AI services, and userfacing applications.
• Lead the development of AIpowered tools, including decision support systems, copilots, internal developer tools, and domainspecific agents.
• Design and maintain robust service architectures (APIs, eventdriven systems, batch and realtime pipelines) optimized for reliability, security, and extensibility.
• Establish engineering best practices across code quality, testing, CI/CD, observability, and performance.
• Collaborate with AI/ML engineers to productionize models and agents, ensuring seamless integration into realworld workflows.
• Partner directly with business leaders and Csuite executives to translate strategic objectives into scalable technical solutions.
• Mentor senior engineers and technical leads, fostering a culture of ownership, craftsmanship, and continuous improvement.

Requirements

• A bachelor’s degree in Computer Science, Engineering, or a related technical field and 5+ years of professional engineering experience; or a graduate degree and approximately 3+ years of relevant experience.
• Demonstrated experience in senior software engineering, platform engineering, or technical leadership roles.
• Strong proficiency in modern software development practices, including APIs, distributed systems, and cloud services.
• Hands on experience deploying AIenabled applications or tooling into production environments.
• Comfort operating in fastpaced, clientfacing environments with evolving requirements.

Qualifications

• You will be expected to:
• Lead development of backend and fullstack systems using modern languages and frameworks (e.g., Python, Java, Scala, TypeScript).
• Design and manage cloudnative architectures on platforms such as AWS or GCP, using containerization and infrastructureascode.
• Build AIready application layers that integrate LLMs, retrieval systems, vector databases, and model orchestration frameworks.
• Develop internal tooling and developer platforms that improve velocity, reliability, and reuse across teams.
• Define and enforce standards for security, privacy, reliability, and compliance (e.g., SOC2, HIPAA, enterprise governance).
• Translate ambiguous business problems into concrete system designs and incremental delivery plans.
• Communicate complex technical concepts clearly to nontechnical stakeholders.

Skills and attributes for success

• Strong engineering judgment, fluency in modern AI tooling, and the ability to operate comfortably across strategy and execution.
• Experience working in management consulting, productled organizations, or highgrowth startups.
• Familiarity with modern AI ecosystems, including LLM frameworks, agent architectures, and prompt/tool orchestration.
• A strong product mindset—understanding not just how to build systems, but how they will be adopted and sustained.
• Knowledge of how to leverage firm-approved AI tools in a business setting, including Microsoft Copilot.

Pay

The base salary range for this job in all geographic locations in the US is $205,000 to $235,000. Individual salaries within those ranges are determined through a wide variety of factors including but not limited to education, experience, knowledge, skills and geography.

Schedule

We expect most people in external, client serving roles to work together in person 40-60% of the time over the course of an engagement, project or year.