Software Engineering Director

Locations: New York, Atlanta, Boston, Chicago, Dallas, Denver, Detroit, Houston, Los Angeles, McLean, Hoboken, Philadelphia, San Francisco, Seattle

At EY, we’re all in to shape your future with confidence. 

We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go.  Join EY and help to build a better working world.

 

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 EY-Parthenon, the Growth Platforms team focuses on building durable technology and AI capabilities that power longterm enterprise growth. The Software Engineering Director for AI Tooling plays a pivotal role in translating strategy into execution—designing and scaling modern software platforms, AIenabled tools, and internal products that create measurable value for Fortune 500 and growthstage clients alike.

This role sits at the intersection of engineering excellence, applied AI, and business impact—partnering closely with executives, product leaders, and multidisciplinary teams to deliver systems that can be adopted, trusted, and scaled.

Your key responsibilities

As a Software Engineering Director, you will lead the design and delivery of productiongrade software systems and AIenabled tooling that underpin highvisibility client engagements and internal platforms. You will own architectural decisions, development standards, and technical direction across multiple workstreams.

Key responsibilities include:

• 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.