Senior AI Enablement Lead — Governance & Reuse

JPMorgan Chase & Co.

Columbus (OH)

On-site

USD 120,000 - 180,000

Full time

5 days ago
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Job summary

JPMorganChase in Columbus, OH seeks a Lead Software Engineer within Corporate Technology and the AI/Machine Learning & Automation Center of Excellence to drive scalable adoption of responsible AI and intelligent automation by defining standards, reference architectures, and governance.

You will influence cross-functional teams, promote reuse, and elevate engineering practices across cloud, APIs, and integration patterns while ensuring security, resilience, and operational readiness of AI-enabled

Qualifications

  • Proven ability to influence senior stakeholders in a large org without direct authority.
  • Strong understanding of AI governance, bias mitigation, and lifecycle management.
  • Experience with enterprise enablement or center of excellence modelos.

Responsibilities

  • Drive enterprise alignment and adoption of AI/ML and intelligent automation across delivery roadmaps.
  • Influence cross-functional stakeholders to align priorities and adhere to Center of Excellence standards.
  • Define and evolve scalable reference architectures and implementation patterns.
  • Enable reuse via shared tooling, accelerators, and reusable capabilities.
  • Provide advisory support to strengthen design decisions and operational readiness of AI solutions.
  • Establish Responsible AI governance across distributed teams and lifecycle management practices.
  • Promote secure, resilient engineering practices aligned to enterprise architecture expectations.

Skills

Stakeholder influence
AI governance
Enterprise architecture
Cloud & APIs

Job description

JPMorganChase in Columbus, OH seeks a Lead Software Engineer within Corporate Technology and the AI/Machine Learning & Automation Center of Excellence to drive scalable adoption of responsible AI and intelligent automation by defining standards, reference architectures, and governance.

You will influence cross-functional teams, promote reuse, and elevate engineering practices across cloud, APIs, and integration patterns while ensuring security, resilience, and operational readiness of AI-enabled

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