Lead AI Agent Engineer for Enterprise Scale

EY; Seattle (WA); Hybrid; USD 126,000 - 262,000; Full time

Benefits offered by this job

Medical and dental coverage

401(k) plan

Paid time off

Job summary

EY is seeking an experienced engineer to build AI agents that move from intent to verified outcomes, operating across complex workflows with clear safety controls. You’ll design the execution loops, tools, context, and evaluations needed for reliable enterprise deployments.

The role sits at the intersection of applied AI, distributed systems, and product engineering, addressing long-running behavior, real enterprise integrations, and challenging production failures.

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.
• Travel and On-site requirements: up to 50% travel and hybrid office.

Responsibilities

• Choose the right execution model and design deterministic steps or single-agent loops when beneficial.
• Build dependable tools with clear contracts, validated outcomes, and controlled errors.
• Engineer agent behavior across planning, routing, delegation, and handoffs in full workflows.
• Create durable context by combining instructions, user state, retrieval, memory, and environment feedback.
• Bound agent authority with scoped identities, credentials, budgets, and emergency containment.
• Evaluate complete trajectories with tests for success, tooling, recovery, and human takeover.
• Operate long-running execution with durable state, checkpointing, and safe retries.
• Make behavior observable with end-to-end traces and replay for failure diagnosis.
• Protect user control with clear intervention points for inspection and resumption.
• Build shared capability by collaborating across product, platform, knowledge, security, and evaluation teams.

Skills

Software engineering

Distributed systems

Python

TypeScript

Applied AI

Model APIs

Retrieval

Memory

Education

Bachelor’s Degree in a relevant field

Tools

Git

Docker

Kubernetes

Job description

EY is seeking an experienced engineer to build AI agents that move from intent to verified outcomes, operating across complex workflows with clear safety controls. You’ll design the execution loops, tools, context, and evaluations needed for reliable enterprise deployments.

The role sits at the intersection of applied AI, distributed systems, and product engineering, addressing long-running behavior, real enterprise integrations, and challenging production failures.