AI Agent Engineering Leader

EY; Miami (FL); Hybrid; USD 126,000 - 262,000; Full time

Benefits offered by this job

Hybrid work model

Total Rewards package including health

Paid time off options

Job summary

EY in the United States is seeking an experienced AI/ML engineer to build long-running agents and enterprise integrations that operate safely in production. You will shape execution loops, tools, and governance across complex workflows, balancing autonomy with controllable outcomes.

This role blends applied AI, distributed systems, and product engineering, demanding hands-on delivery of model-driven workflows, reliable tooling, and measurable improvements to real business processes.

Qualifications

• Bachelor’s Degree in a relevant field of study.
• 7-9 years of 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.
• Applied AI patterns: model APIs, structured outputs, retrieval, tool use, and evaluation of variable behavior.
• Distributed execution: asynchronous work, state, concurrency, idempotency, retries, and failure recovery.
• Identity and controls: access boundaries and scoped authority for applications or automated workloads.
• Production learning: improving live systems through traces, metrics, logs, incident analysis, and durable remediation.
• Travel and On-site requirements: up to 50% travel and hybrid capacity.

Responsibilities

• Choose the right execution model for agent architectures with measured complexity.
• Build dependable tools with clear contracts, validated outcomes, and safe error handling.
• Engineer agent behavior across planning, routing, delegation, stopping, retry, and handoff.
• Create durable context using instructions, user state, retrieval, memory, and environment feedback.
• Bound agent authority with scoped identities, credentials, and budgets.
• Evaluate complete trajectories with tests for verified task success and recovery.
• Operate long-running execution with durable state, checkpointing, and graceful degradation.
• Make behavior observable with end-to-end traces and replay for failure diagnosis.
• Protect user control with clear intervention points for inspection and resume.
• Build shared capability by partnering across teams and publishing reusable patterns.

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 in the United States is seeking an experienced AI/ML engineer to build long-running agents and enterprise integrations that operate safely in production. You will shape execution loops, tools, and governance across complex workflows, balancing autonomy with controllable outcomes.

This role blends applied AI, distributed systems, and product engineering, demanding hands-on delivery of model-driven workflows, reliable tooling, and measurable improvements to real business processes.