AI Execution & Reporting Lead

EY

Lansing (MI)

Hybrid

USD 157,000 - 311,000

Full time

9 days ago

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Benefits offered by this job

Medical and dental coverage

Pension and 401(k)

Paid time off

Flexible vacation policy

Job summary

EY is seeking an Associate Director of Information Security AI engineering to lead the application of AI, including agentic workflows with Claude, Python, and Power Platform, across a global technology program. You will drive the AI and automation roadmap, ensure secure and verifiable outputs, and mentor teams in delivering trusted AI-enabled security services.

This senior role requires deep technical ownership, cross-functional collaboration, and the ability to set standards for AI use within a

Qualifications

At least 10 years of experience in software, automation or data engineering, with production ownership.
Proven experience building production solutions with Claude, including Claude Code and the Claude Agent SDK.
Experience designing end-to-end agentic workflows that automate tasks.
Practical prompt and context engineering with reliable, repeatable model output.
Strong Python programming for document and data workflows.
Experience with Power Platform tools and enterprise workflow automation.
Track record of automating recurring operational or reporting processes end to end.
Experience building unattended systems with robust error handling and logging.
Experience reconciling large datasets from multiple systems.
Experience setting technical standards and documented patterns.

Responsibilities

Design, build and operate AI agents and automation that produce recurring program reports.
Own the AI and automation roadmap for the program, prioritizing impact and risk reduction.
Guide teams on applying AI within Technology Assurance, Risk and Policy.
Establish safe, consistent AI adoption and verification practices across the function.
Define how AI output is verified, including reconciliation against source data.
Set engineering standards for AI use, including prompts, context and testing.
Advise leadership on when AI is appropriate and on cost and risk.
Evaluate new AI tooling and models for program value.
Build resilient, maintainable automation with proper credential management and logging.
Collaborate with IT and Information Security for approval and ongoing support.
Represent the program to senior stakeholders and governance forums.
Develop AI engineering capability with reusable components and patterns.