Senior AI Agent Engineering Manager

EY

Salem (OR)

Hybrid

USD 144,000 - 329,000

Full time

5 days ago
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Benefits offered by this job

Medical and dental coverage
Pension and 401(k)
Paid time off

Job summary

EY is seeking a senior engineering professional to build AI agents that operate across complex workflows with verifiable outcomes. You will design execution loops, tools, and runtime controls, balancing autonomy with safety for enterprise-scale deployments.

The role sits at the intersection of applied AI, distributed systems, and product engineering, tackling long-running behaviors, real-world integrations, and difficult production failures with a focus on observable, secure, and controllable

Qualifications

  • Strong software engineering and distributed-systems judgment.
  • Experience shipping large-language-model applications or agent workflows.
  • Hands-on with model APIs, structured outputs, and tool use.

Responsibilities

  • Choose the right execution model for deterministic vs autonomous behavior.
  • Build dependable tools with clear contracts and error handling.
  • Engineer agent behavior across planning, routing, delegation, retries, and handoff.
  • Create durable context with state, memory, and environment feedback.
  • Bound agent authority with scoped identities and budgets.
  • Evaluate complete trajectories with tests for verified tasks and recovery.
  • Operate long-running execution with durable state and safe retries.
  • Make behavior observable with end-to-end tracing and replay.
  • Protect user control with clear intervention points.
  • Build shared capability across teams and publish reusable patterns.

Skills

Production engineering
Agent architecture
AI application depth
Evaluation discipline
Security and operability
Product judgment
Python
TypeScript

Education

Bachelor’s Degree in a relevant field

Job description

EY is seeking a senior engineering professional to build AI agents that operate across complex workflows with verifiable outcomes. You will design execution loops, tools, and runtime controls, balancing autonomy with safety for enterprise-scale deployments.

The role sits at the intersection of applied AI, distributed systems, and product engineering, tackling long-running behaviors, real-world integrations, and difficult production failures with a focus on observable, secure, and controllable

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