Applied AI ML Executive Director, Chief Data & Analytics Office

JPMorgan Chase

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Quick summary

Work type: On-site
Location: Jersey City, NJNew York, NY
Employment: Full-time
Posted: 75 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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Similar $234k

$163k $299k

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This listing doesn't post a salary. Most similar roles pay $202,600–$265,250.

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About JPMorgan Chase

JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.

JPMorgan Chase currently has 1226 open roles on FindRole.

Listed pay typically runs $156,750–$215,000 across 5 roles with salary data.

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At a glance

TL;DR · Applied AI ML Executive Director, Chief Data & Analytics Office

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The Applied AI ML Executive Director, Chief Data & Analytics Office leads a team within the Chief Administrative Office to design, build, and scale Generative AI and agentic AI capabilities. This role involves architecting end-to-end solutions that automate complex operational workflows, developing multi-agent systems to orchestrate tasks, and building reusable frameworks, libraries, and services for enterprise-wide adoption. The position requires establishing production engineering rigor, including observability, performance tuning, and incident readiness. Key technical requirements include expertise in distributed computing patterns for model training and serving, state persistence, and MLOps or LLMOps practices. Candidates should possess experience with Amazon Web Services, specifically Amazon SageMaker and Amazon Bedrock. The role focuses on translating business objectives into robust AI/ML products while ensuring reliability, security, and long-term maintainability.

Skills

Generative AI Agentic AI Machine Learning MLOps LLMOps Amazon Web Services Amazon SageMaker Amazon Bedrock Distributed Computing Model Serving Observability Production Engineering Data Analysis

What you'll do

Architect end-to-end Generative AI and agentic AI solutions to automate complex operational workflows.
Lead the design and delivery of multi-agent systems that orchestrate tasks and execute workflows at scale.
Translate business objectives into robust AI/ML product capabilities while ensuring reliability, security, and maintainability.
Build reusable frameworks and services to standardize model development, evaluation, deployment, and monitoring for other teams.
Establish production engineering rigor including observability, performance tuning, incident readiness, and operational runbooks.
Partner with stakeholders to identify high-value opportunities, define success metrics, and drive enterprise-scale transformation.
Mentor a high-performing team of AI engineers and researchers to foster a culture of technical excellence.
Drive governance for experimentation to improve model and agent behavior through continuous feedback loops.

What we're looking for

PhD in Computer Science or a related quantitative discipline with 8+ years of relevant experience.
MS in Computer Science or a related field with 12+ years of relevant experience.
Formal training or certification in applied AI and machine learning concepts.
Proven track record of deploying AI/ML applications into production environments at scale.
Strong understanding of AI/ML fundamentals, including experimental design, evaluation methods, and data analysis techniques.
Experience with distributed computing patterns for model training, model serving, and state persistence in production systems.
Demonstrated experience building, mentoring, and leading high-performing AI/ML teams delivering complex outcomes.
Experience deploying and operating models on Amazon Web Services platforms, including Amazon SageMaker and/or Amazon Bedrock (preferred).

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