Lead AI Architect – Multi-Agent Systems & Control

EY; Raleigh (NC); On-site; USD 144,000 - 329,000; Full time

Benefits offered by this job

Hybrid/Remote work options

Total Rewards package

Paid time off

Job summary

EY is seeking an experienced Lead AI Software Architect to guide a team of domain architects in designing and implementing AI Agent Control. The role focuses on agent authentication, observability, and scalable agentic systems across environments, including post-training and federated learning.

The ideal candidate will lead the development of universal control harnesses, mentor engineers, and collaborate with security, data, and infrastructure teams to deliver impactful AI capabilities at scale.

Qualifications

• Advanced degree in Electrical Engineering, Computer Science or Mathematics is required.
• 10+ years of experience in software engineering and AI.
• Experience with multi-agent systems and modern secrets management.
• Familiarity with Nvidia NVAIE, AWS and MSFT Azure AI stacks.

Responsibilities

• Design control harness intelligence systems for multiagent environments.
• Architect agent identity and authentication for large-scale systems.
• Oversee post-training and tuning/customization environments.
• Develop synthesis models for AI open-source models.
• Implement architectures and benchmark against evals.
• Collaborate with AI, Security, Data and Infra teams to ensure practical outcomes.
• Lead development of universal agentic control harnesses.
• Present at conferences and support IP development.
• Hands-on development of advanced AI capabilities in agent control.

Skills

Analytical thinking

Leadership

Cross-functional collaboration

Emotional intelligence

Problem solving

Mentoring

Cybersecurity awareness

Education

Advanced degree in Electrical Engineering, Computer Science or Mathematics

Tools

Cursor

Claude Code

Qodo/Codium

Gemini

AWS Q

GitHub

Job description

EY is seeking an experienced Lead AI Software Architect to guide a team of domain architects in designing and implementing AI Agent Control. The role focuses on agent authentication, observability, and scalable agentic systems across environments, including post-training and federated learning.

The ideal candidate will lead the development of universal control harnesses, mentor engineers, and collaborate with security, data, and infrastructure teams to deliver impactful AI capabilities at scale.