Head of AI Agent Engineering

EY; Tucson (AZ); Hybrid; USD 126,000 - 230,000; Full time

Benefits offered by this job

Medical and dental coverage

401(k) plan

Paid time off

Flexible vacation policy

EY Paid Holidays

Job summary

EY is seeking a lead for building AI agents at scale, blending applied AI with distributed systems and product engineering. You will shape deterministic workflows, long-running executions, and enterprise integrations while ensuring safety and steerability.

The role blends execution, evaluation, and operations across diverse teams in a hybrid US office footprint. You will own design of planning, tools, context, and containment, and drive durable, observable agent behavior with strong focus on

Qualifications

• Bachelors degree in a relevant field of study.
• 7-9 years of experience in software or applied machine-learning engineering with ownership of production systems.
• Hands-on evidence of shipping large-language-model applications, agents, or complex model-driven workflows.
• 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.
• Build dependable tools with clear contracts and validated outcomes.
• Engineer agent behavior across planning, routing, delegation, and retry.
• Create durable context from instructions, user state, retrieval, memory, and environment feedback.
• Bound agent authority with scoped identities, credentials, and budgets.
• Evaluate complete trajectories with tests measuring verified task success and tool use.
• Operate long-running execution with durable state, checkpointing, and safe retries.
• Make behavior observable with end-to-end traces and replays.
• Protect user control with intervention points to inspect and resume work.
• Build shared capability by partnering across teams and publishing reusable patterns.

Skills

Python

TypeScript

Distributed systems

AI applications

Evaluation discipline

Security and operability

Product judgment

Education

Bachelors Degree

Tools

MCP

Knowledge graphs

Context services

Job description

EY is seeking a lead for building AI agents at scale, blending applied AI with distributed systems and product engineering. You will shape deterministic workflows, long-running executions, and enterprise integrations while ensuring safety and steerability.

The role blends execution, evaluation, and operations across diverse teams in a hybrid US office footprint. You will own design of planning, tools, context, and containment, and drive durable, observable agent behavior with strong focus on