Senior Manager, Agentic AI Engineering

EY; Orlando (FL); Hybrid; USD 144,000 - 374,000; Full time

Job summary

EY invites senior software and applied AI engineers to join Challenger and shape the future of enterprise AI. You will build deterministic agent workflows, durable state management, and safe runtime controls that scale across complex enterprise integrations, while maintaining clarity and safety when systems fail.

The role sits at the intersection of applied AI, distributed systems, and product engineering, focusing on long-running behavior, real-world deployments, and challenging production

Qualifications

• Bachelor’s degree in a relevant field.
• 9+ years of relevant experience in software or applied ML engineering.
• Hands-on shipping of LLM apps, agents, or complex workflows.
• Strong production skills in Python, TypeScript, or equivalent.
• Experience with model APIs, tool use, and evaluation of variable behavior.

Responsibilities

• Choose execution models and design agent architectures with measured complexity.
• Build dependable tools and interfaces with clear contracts.
• Engineer agent behavior across complete workflows.
• Create durable context with state and memory while preserving access.
• Bound agent authority with scoped identities and budgets.
• Evaluate trajectories with tests for verified task success and recovery.
• Operate long-running execution with durable state and safe retries.
• Make behavior observable with end-to-end traces and replay.
• Protect user control with clear intervention points.
• Build shared capability through cross-functional collaboration.

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 invites senior software and applied AI engineers to join Challenger and shape the future of enterprise AI. You will build deterministic agent workflows, durable state management, and safe runtime controls that scale across complex enterprise integrations, while maintaining clarity and safety when systems fail.

The role sits at the intersection of applied AI, distributed systems, and product engineering, focusing on long-running behavior, real-world deployments, and challenging production