AI Agent Engineering Manager

EY; Richmond (VA); Hybrid; USD 126,000 - 230,000; Full time

Benefits offered by this job

Medical and dental coverage

401(k) plan and pension

Paid time off options

Job summary

EY seeks an experienced AI/Applied ML engineer to build long‑running agent systems that operate across complex workflows. You will design deterministic loops, orchestrate tools and context, and ensure safe, steerable behavior while handling failure modes.

You will integrate with enterprise systems, ship model‑driven workflows, and balance autonomy with user control. This role embraces hybrid work with travel up to 50% and opportunities to impact multiple EY service lines.

Qualifications

• Bachelor’s Degree in a relevant field of study.
• 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.
• This role requires up to 50% travel and hybrid office attendance.

Responsibilities

• Choose the right execution model for agent architectures with measurable performance.
• Build dependable tools with clear contracts, validated outcomes, and narrow authorization.
• Engineer agent behavior, routing, delegation, stopping, retry, and handoffs across workflows.
• Create durable context by combining instructions, user state, retrieval, memory and environment feedback.
• Bound agent authority with scoped identities, credentials, budgets and approval points.
• Evaluate complete trajectories with tests for task success, tool use, recovery, and human takeover.
• Operate long‑running execution using durable state, checkpointing, and graceful degradation.
• Make behavior observable with end‑to‑end traces and production analysis.
• Protect user control with clear intervention points for inspection and safe resume.
• Build shared capability by publishing reusable agent patterns and lessons.

Skills

Production engineering

Agent architecture

AI application depth

Evaluation discipline

Security and operability

Product judgment

Education

Bachelor’s Degree in a relevant field

Tools

Python

TypeScript

Job description

EY seeks an experienced AI/Applied ML engineer to build long‑running agent systems that operate across complex workflows. You will design deterministic loops, orchestrate tools and context, and ensure safe, steerable behavior while handling failure modes.

You will integrate with enterprise systems, ship model‑driven workflows, and balance autonomy with user control. This role embraces hybrid work with travel up to 50% and opportunities to impact multiple EY service lines.