Senior AI Agent Engineer - Lead Complex Workflows

EY; Dallas (TX); Hybrid; USD 144,000 - 359,000; Full time

Job summary

EY is exploring Challenger, building AI agents that operate across complex workflows with safety and observability. The role sits at the intersection of applied AI, distributed systems, and product engineering, delivering enterprise-grade, maintainable automation.

The team emphasizes reusable patterns, risk-aware design, and long-term reliability, with opportunities to influence across product and security teams while enabling scalable services. A hybrid office approach is common.

Qualifications

• Bachelor’s Degree in a relevant field.
• 9-12+ years of relevant experience.
• Strong software or applied ML engineering with production systems.
• Hands-on evidence of shipping LLM apps, agents, or complex model-driven workflows.
• Proficiency in Python, TypeScript, or other production languages.
• Experience with model APIs, structured outputs, retrieval, tools and evaluation.
• Experience with asynchronous work, state, concurrency, retries.
• Experience implementing access boundaries and scoped authority.
• Proven ability to improve live systems via traces, metrics, logs, incidents.
• Willingness to travel up to 50% and work in a hybrid capacity.

Responsibilities

• Choose the right execution model for agent architectures with deterministic steps or multi-agent coordination as justified.
• Build dependable tools with clear contracts and validated outcomes.
• 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, budgets, approvals and containment.
• Evaluate complete trajectories with tests measuring task success, tool use, and recovery.
• Operate long-running execution with durable state, checkpointing, and safe retries.
• Make behavior observable via 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, security and evaluation teams.

Skills

Production engineering

Agent architecture

AI application depth

Evaluation discipline

Security and operability

Product judgment

Education

Bachelor’s Degree in a relevant field

Job description

EY is exploring Challenger, building AI agents that operate across complex workflows with safety and observability. The role sits at the intersection of applied AI, distributed systems, and product engineering, delivering enterprise-grade, maintainable automation.

The team emphasizes reusable patterns, risk-aware design, and long-term reliability, with opportunities to influence across product and security teams while enabling scalable services. A hybrid office approach is common.