AI Agent Engineering Manager — Hybrid/Remote

EY; Akron (OH); Hybrid; USD 126,000 - 230,000; Full time

Job summary

EY is seeking an experienced AI/Applied ML Engineer to design and operate durable, safe autonomous agents across enterprise workflows. You will own end-to-end pipelines from intent to verified outcomes, integrating tools, memory, and governance with a focus on reliability and user control.

You will work at the intersection of applied AI, distributed systems, and product engineering, shaping long-running executions, enterprise integrations, and production readiness across Challenger initiatives.

Qualifications

• Bachelor’s Degree in a relevant field of study.
• Evidence of production systems ownership and live behavior.
• Experience with model APIs, structured outputs, and tool use.

Responsibilities

• Choose the right execution model for deterministic vs. autonomous workflows.
• Build dependable tools and interfaces with clear contracts and safe errors.
• Engineer agent behavior including planning, routing, delegation, retries, and handoffs.
• Create durable context combining instructions, user state, memory, and environment feedback.
• Bound agent authority with scoped identities, credentials, budgets, and approvals.
• Evaluate complete trajectories with tests for verified task success and recovery.
• Operate long-running execution with durable state, checkpoints, and graceful degradation.
• Make behavior observable with end-to-end traces and production analysis.
• Protect user control with clear intervention points for inspection or redirection.
• Build shared capability by partnering across teams and publishing reusable patterns.

Skills

Production eng

Agent architecture

AI depth

Evaluation

Security

Product judgment

Education

Bachelor’s Degree in a relevant field of study

Job description

EY is seeking an experienced AI/Applied ML Engineer to design and operate durable, safe autonomous agents across enterprise workflows. You will own end-to-end pipelines from intent to verified outcomes, integrating tools, memory, and governance with a focus on reliability and user control.

You will work at the intersection of applied AI, distributed systems, and product engineering, shaping long-running executions, enterprise integrations, and production readiness across Challenger initiatives.