Vice President - Applied AI Integration Lead

JPMorgan Chase & Co.

Manila

On-site

PHP 2,000,000 - 3,500,000

Full time

3 days ago
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Job summary

JPMorgan Chase & Co. in Manila seeks an Applied AI integration lead to partner with product and business teams, turning AI ideas into prototypes, playbooks, and enablement that improve customer, employee, and operational outcomes.

You will run experiments, build prototypes, and guide leadership on practical AI strategy with a strong emphasis on responsible adoption. You will also help steward governance and collaborate across engineering, data, and platform teams to transition validated

Qualifications

  • 3 years of experience helping teams integrate emerging technology into business workflows or products.
  • Experience designing and running experiments or pilots with measurable success metrics.
  • Experience building prototypes or tools that apply ML to business problems.
  • Experience creating learning content and facilitating workshops for professional audiences.
  • Ability to translate ambiguous strategy into scoped, prioritized work.
  • Strong stakeholder management skills, including communicating trade-offs, risks, and recommendations.

Responsibilities

  • Lead discovery with partners to identify high-impact opportunities where AI can improve outcomes.
  • Design and run experiments to evaluate AI use cases using measurable success criteria (quality, cycle time, risk reduction, cost, customer experience).
  • Build and iterate prototypes and lightweight tools that demonstrate value and inform production decisions.
  • Partner with engineering, data, and platform teams to transition validated prototypes into production-ready solutions.
  • Establish and maintain a prioritized, business-driven pipeline of AI ideas, including intake, triage, routing, and status visibility.
  • Create and deliver a tiered enablement program through workshops and reusable learning content.
  • Provide consultation to teams on selecting fit-for-purpose AI approaches and integrating solutions into workflows.
  • Define and track adoption and impact metrics, and communicate outcomes to stakeholders and leadership.
  • Promote responsible AI practices by aligning delivery with risk and governance expectations.
  • Stay current on industry trends and assess new techniques for applicability to business problems.
  • May lead a team with coaching and direction across initiatives.

Skills

AI integration
Experiment design
Prototype development
Workshop facilitation
Strategy translation
Stakeholder management
ML knowledge

Job description

Build what's next by helping teams turn emerging AI into measurable outcomes. In this role, you will partner across product and business teams to test ideas quickly, prove value, and scale what works. You will translate real needs into practical prototypes, playbooks, and enablement that lift how work gets done. You will also help shape responsible ways of working so AI is adopted safely and consistently. If you enjoy combining strategy, hands‑on building, and coaching others, this role is for you.

Job summary

As an Applied AI integration lead in Home Lending, you help teams across product and the business get more from AI. You run experiments to identify what improves outcomes, scale successful patterns through enablement and prototypes, and advise leaders on practical AI strategy. You also help steward responsible adoption by partnering with governance and technology stakeholders.

Job responsibilities
  • Lead discovery with partners to identify high-impact opportunities where AI can improve customer, employee, or operational outcomes
  • Design and run experiments to evaluate AI use cases using measurable success criteria (e.g., quality, cycle time, risk reduction, cost, or customer experience)
  • Build and iterate prototypes and lightweight tools that demonstrate value and inform production decisions
  • Partner with engineering, data, and platform teams to transition validated prototypes into production-ready solutions when appropriate
  • Establish and maintain a prioritized, business-driven pipeline of AI ideas, including intake, triage, routing, and status visibility
  • Create and deliver a tiered enablement program (baseline learning, practitioner level, advanced builders) through workshops and reusable learning content
  • Provide consultation to teams on selecting fit-for-purpose AI approaches and integrating solutions into existing workflows
  • Define and track adoption and impact metrics, and communicate outcomes and learnings to stakeholders and leadership
  • Promote responsible AI practices by aligning delivery with applicable risk, governance, and control expectations
  • Stay current on industry and technology trends, and assess new techniques for applicability to business problems
  • May lead a team, including coaching, mentoring, and setting direction across multiple initiatives
Required qualifications, capabilities and skills
  • 3 years of experience helping teams integrate emerging technology into business workflows or products
  • Demonstrated experience designing and running experiments or pilots with clear success metrics
  • Demonstrated experience building prototypes or tools that apply machine learning or related techniques to business problems
  • Experience creating learning content and facilitating workshops for professional audiences
  • Ability to translate ambiguous strategy into scoped, prioritized work and actionable plans
  • Strong stakeholder management skills, including communicating trade-offs, risks, and recommendations to diverse audiences
  • Working knowledge of common AI/ML application areas such as natural language processing, speech recognition, or time series forecasting
Preferred qualifications, capabilities and skills
  • Experience scaling enablement, accelerator, or adoption programs across multiple teams
  • Experience partnering with governance, risk, controls, or similar stakeholders to support responsible AI delivery
  • Experience leading multiple initiatives in parallel, including coordinating work across cross-functional teams
  • Experience building evaluation approaches for AI solutions (e.g., quality metrics, testing design, monitoring considerations)
  • Experience presenting learnings and recommendations to senior stakeholders in clear, practical terms
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