Senior AI Platform Architect - Forward Deployed

EY; Tampa (FL); Hybrid; USD 144,000 - 329,000; Full time

Benefits offered by this job

Hybrid work model

Medical and dental coverage

Job summary

EY is seeking a Forward Deployed Engineer – Applied AI at Senior Manager level for Financial Services. The role defines AI system design principles, leads cross‑team delivery, and ensures scalable, secure AI/ML platforms aligned with business needs.

You will mentor senior engineers, shape enterprise integration, and guide adoption of modern AI tooling to accelerate delivery and maintain governance across large-scale deployments.

Qualifications

• Ability to translate complex enterprise challenges into strategic AI architecture decisions.
• Deep knowledge of foundation models and their enterprise applicability.
• Experience leading multi-team AI architecture programs.
• Hands-on engineering credibility in Python and modern AI tooling.
• Subject matter authority on knowledge AI systems and applications.

Responsibilities

• Define system design principles, reference architectures, and engineering patterns for AI/ML initiatives.
• Lead complex technical challenges across teams with hands-on guidance.
• Own end-to-end architecture for strategic AI initiatives and governance.
• Drive engineering standards, observability, security, and responsible AI practices.
• Shape API/integration strategies and decouple clients from internal AI topology.

Skills

AI architecture

Python

Leadership

Enterprise AI

Stakeholder management

Education

Bachelor’s degree preferred

Tools

Claude Code

Codex

LangGraph

LangChain

Job description

EY is seeking a Forward Deployed Engineer – Applied AI at Senior Manager level for Financial Services. The role defines AI system design principles, leads cross‑team delivery, and ensures scalable, secure AI/ML platforms aligned with business needs.

You will mentor senior engineers, shape enterprise integration, and guide adoption of modern AI tooling to accelerate delivery and maintain governance across large-scale deployments.