AI Agent Architect & Manager

EY; Tallahassee (FL); Hybrid; USD 126,000 - 230,000; Full time

Job summary

EY seeks an experienced AI/ML engineer to build long‑running agents that move from intent to verified outcomes. You’ll design deterministic loops, check-pointed state, and safe autonomy across enterprise integrations.

You will tackle complex production failures, balance operational cost with user experience, and help evolve Challenger’s shared technology and governance. Hybrid office with up to 50% travel is expected.

Qualifications

• Bachelor’s Degree in a relevant field.
• 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.
• Distributed execution: asynchronous work, state, concurrency, idempotency, retries, and failure recovery.
• Identity and controls: access boundaries and scoped authority for applications or automated workloads.
• Travel and On-site requirements: up to 50% travel with hybrid office capability.

Responsibilities

• Choose the right execution model and design agent architectures with measurable performance requirements.
• Build dependable tools with clear contracts, validated outcomes, and secure error handling.
• Engineer agent behavior including planning, routing, delegation, stopping, retry, and handoff across workflows.
• Create durable context by combining instructions, user state, retrieval, memory, and environment feedback.
• Bound agent authority with scoped identities, credentials, budgets, and approval points.
• Evaluate complete trajectories with tests measuring task success, tool use, recovery, and human takeover.
• Operate long-running execution with durable state, checkpoints, and graceful degradation.
• Make behavior observable with end-to-end tracing and replay to diagnose failures.

Skills

Production engineering

Agent architecture

AI application depth

Evaluation discipline

Security and operability

Product judgment

Travel readiness

Education

Bachelor’s degree in a relevant field

Tools

Python

TypeScript

Job description

EY seeks an experienced AI/ML engineer to build long‑running agents that move from intent to verified outcomes. You’ll design deterministic loops, check-pointed state, and safe autonomy across enterprise integrations.

You will tackle complex production failures, balance operational cost with user experience, and help evolve Challenger’s shared technology and governance. Hybrid office with up to 50% travel is expected.