AI Agent Engineering Manager

EY; Memphis (TN); Hybrid; USD 126,000 - 251,000; Full time

Job summary

EY's Challenger program invites you to build AI agents that operate across complex workflows with determinism and safety, enabling enterprise integrations and reliable production behavior.

You’ll work at the intersection of applied AI, distributed systems, and product engineering, shaping long-running behavior, failure handling, and measurable improvements.

This role requires up to 50% travel with hybrid office options across the US; EY offers a broad rewards program and professional growth.

Qualifications

• Bachelor’s Degree in a relevant field.
• 7-9 years of experience in software or applied machine-learning engineering, with ownership of production systems and their live behavior.
• Hands-on evidence of shipping large-language-model applications, agents, or complex model-driven workflows used for real work.
• Strong capability in Python, TypeScript, or another language used for production services and integrations.
• Experience with model APIs, structured outputs, retrieval, tool use, and evaluation of variable behavior.
• Practical command of asynchronous work, state, concurrency, idempotency, retries, and failure recovery.
• Experience implementing access boundaries and scoped authority for applications or automated workloads.
• Evidence of improving live systems through traces, metrics, logs, incident analysis, and durable remediation.
• Travel up to 50% and hybrid office capacity

Responsibilities

• Choose the right execution model for deterministic or coordinated agents.
• Build dependable integration tools with clear contracts and narrow authorization.
• Engineer agent behavior across planning, routing, delegation, and handoffs.
• Create durable context from instructions, user state, memory, and feedback.
• Bound agent authority with scoped identities, budgets, and approvals.
• Evaluate complete trajectories with tests for verified outcomes.
• Operate long-running execution with durable state and safe retries.
• Make behavior observable with traces and replay for debugging.
• Protect user control with intervention points for inspection.
• Build shared capability with cross-team collaboration and reusable patterns

Skills

Production engineering

Agent architecture

AI application depth

Evaluation discipline

Security and operability

Product judgment

Education

Bachelor’s Degree

Tools

Python

TypeScript

Job description

EY's Challenger program invites you to build AI agents that operate across complex workflows with determinism and safety, enabling enterprise integrations and reliable production behavior.

You’ll work at the intersection of applied AI, distributed systems, and product engineering, shaping long-running behavior, failure handling, and measurable improvements.

This role requires up to 50% travel with hybrid office options across the US; EY offers a broad rewards program and professional growth.