EY-Parthenon - Strategy and Execution - Growth Platforms - Software Engineer - Sr Assoc/Consultant

About the role

EY-Parthenon’s unique combination of transformative strategy, transactions, and corporate finance delivers real-world value. The Software Engineering Director for AI Tooling role plays a pivotal role in designing and scaling modern software platforms, AI-enabled tools, and internal products that create measurable value for Fortune 500 and growth-stage clients.

Responsibilities

• Architect, build, and scale core software platforms that integrate data, AI services, and user-facing applications.
• Assist in the development of AI-powered tools, including decision support systems, copilots, internal developer tools, and domain-specific agents.
• Design and maintain robust service architectures (APIs, event-driven systems, batch and real-time 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 real-world workflows.

Skills and Attributes

• Strong engineering judgment, fluency in modern AI tooling, and the ability to operate comfortably across strategy and execution.
• Assist in the development of backend and full-stack systems using modern languages and frameworks (e.g., Python, Java, Scala, TypeScript).
• Build AI-ready 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 non-technical stakeholders.

Qualifications

• Outstanding academic performance, with a bachelor's degree and at least 2 years of related work experience; or a graduate degree and approximately 18 months of related work experience.
• Strong proficiency in modern software development practices, including APIs, distributed systems, and cloud services.
• Hands-on experience deploying AI-enabled applications or tooling into production environments.
• Comfort operating in fast-paced, client-facing environments with evolving requirements.
• The ability and willingness to travel and work in excess of standard hours when necessary.
• Experience working in management consulting, product-led organizations, or high-growth 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.