AI Product Engineer Manager — End-to-End, User-Driven

EY

Columbus (OH)

Hybrid

USD 125,000 - 230,000

Full time

6 hours ago
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Benefits offered by this job

Medical and dental coverage
Pension and 401(k) plans
Flexible vacation policy
Paid time off

Job summary

EY invites you to join Challenger, a fast-moving EY program to turn AI ideas into durable products. You’ll be an end-to-end builder close to users, product decisions, and production code, delivering value through practical, testable AI evidence.

You’ll work in a hybrid setting with up to 50% travel, collaborating across product, design, domain, and control teams to ship impactful software responsibly and at scale, shaping the next generation of services with reusable patterns and guardrails that

Qualifications

  • 7+ years of relevant and applicable experience.
  • Bachelor’s Degree in a relevant field of study.
  • End-to-end delivery: A record of taking customer- or employee-facing software from an unclear concept through launch, learning, and adoption.
  • Technical breadth: Strong full-stack capability across modern frontend, backend, API, data, and cloud technologies, demonstrated through shipped work.
  • Applied AI experience: Hands-on experience building products with large language models, retrieval, tools, or comparable AI application patterns.
  • Evaluation experience: Evidence of automated testing and behavioral evaluation for systems with variable or probabilistic outputs.
  • Live-service ownership: Demonstrated responsibility for telemetry, debugging, reliability, incident response, recovery, and performance improvement.
  • User-centered practice: Experience working directly with users, designers, and product leaders to turn evidence into better product decisions.
  • Engineering craft: A consistent record of clear specifications, maintainable code, thoughtful review, and sound technical trade-offs.
  • This role requires up to 50% travel and flexibility to go into the office in a hybrid capacity.

Responsibilities

  • Start with the user. Work directly with users and domain experts to understand real workflows, observe friction, and identify where AI can create distinctive value.
  • Test assumptions quickly. Turn product hypotheses into concise specifications, prototypes, and small releases that generate useful evidence early.
  • Own complete product slices. Build coherent verticals across the experience, services, data, AI behavior, and enterprise integrations rather than optimizing a single layer.
  • Shape AI behavior. Design instructions, context, retrieval, structured outputs, and tool use, choosing adaptation or tuning only when evidence supports it.
  • Build the evidence system. Create representative tasks and automated evaluations that show whether the product is useful, correct, safe, accessible, and improving.
  • Connect outcomes to behavior. Instrument user journeys so the team can relate adoption and task success to system behavior, latency, failures, and cost.
  • Engineer for responsible use. Build clear permission boundaries, secure data handling, human checkpoints, graceful degradation, recovery, and rollback into the experience.
  • Own production quality. Release incrementally, monitor live behavior, respond to incidents, and turn failures into durable product and engineering improvements.
  • Make practical trade-offs. Balance experience, quality, speed, reliability, and cost, using deterministic software when it is the more dependable choice.
  • Contribute reusable patterns. Share proven components and evaluation assets with the broader platform while remaining accountable for their performance in the product workflow.

Skills

Full-stack engineering
AI application depth
Product judgment
Evaluation discipline
Production ownership
High-agency collaboration

Education

Bachelor’s Degree in a relevant field

Job description

EY invites you to join Challenger, a fast-moving EY program to turn AI ideas into durable products. You’ll be an end-to-end builder close to users, product decisions, and production code, delivering value through practical, testable AI evidence.

You’ll work in a hybrid setting with up to 50% travel, collaborating across product, design, domain, and control teams to ship impactful software responsibly and at scale, shaping the next generation of services with reusable patterns and guardrails that

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