Head AI Architect: Memory & Multi-Agent Systems Lead

EY; Baltimore (MD); On-site; USD 144,000 - 329,000; Full time

Benefits offered by this job

Hybrid work model

Medical and dental coverage

Pension and 401(k)

Paid time off options

Job summary

EY is hiring an experienced Lead AI Software Architect to design and implement memory architectures and data fabrics for complex enterprise use cases. You will lead a team of AI Architects and drive multi-agent memory design patterns across AI-native systems.

You will work on RAG, semantic chunking, context design, distributed inference, and frontier models, shaping scalable AI solutions in fast-paced environments while collaborating with security, data, and infrastructure teams.

Qualifications

• Advanced degree in Electrical Engineering, Computer Science or Mathematics.

Responsibilities

• Design memory architectures for multi-agent systems.
• Design context systems including RAG and semantic search.
• Implement and test architectures benchmarking performance.
• Design replicable integration frameworks across systems.
• Drive agent design requirements through AI Native design process.
• Assess emerging memory architectures and frontier models.
• Collaborate with AI, Security, Data and Infrastructure teams.
• Support strategic business development for emerging technology.
• Present at academic conferences and support IP filings.
• Hands-on coding and mentoring Knowledge/Data team.
• Lead a group building Knowledge and data systems for Knowledge AI.

Skills

Analytical skills

Leadership

Cross-functional collaboration

Emotional intelligence

Critical thinking

Problem solving

Education

Advanced degree in Electrical Engineering/Computer Science/Mathematics

Tools

Cursor/Claude Code

Qodo/Codium

Gemini

AWS Q

GitHub

NVIDIA NVAIE

Azure AI

Job description

EY is hiring an experienced Lead AI Software Architect to design and implement memory architectures and data fabrics for complex enterprise use cases. You will lead a team of AI Architects and drive multi-agent memory design patterns across AI-native systems.

You will work on RAG, semantic chunking, context design, distributed inference, and frontier models, shaping scalable AI solutions in fast-paced environments while collaborating with security, data, and infrastructure teams.