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$202,800–$266,850.
Based on 239 similar postings.
Employer
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
1117 open roles
on FindRole.
Listed pay typically runs
$186,160–$215,000
across 7 roles with salary data.
As the Applied AI ML Executive Director, Chief Data & Analytics Office, you will lead a high-performing team of engineers and researchers to design, build, and scale Generative AI and agentic AI capabilities. You will be responsible for architecting end-to-end solutions that automate complex operational workflows, developing multi-agent systems to orchestrate tasks, and building reusable frameworks and services to standardize model development, evaluation, and deployment. Your role involves establishing production engineering rigor, including observability and performance tuning, while partnering with stakeholders to translate business objectives into robust platform capabilities. You will utilize skills in distributed computing, MLOps, and LLMOps, with a focus on Amazon Web Services platforms like SageMaker and Bedrock. The work focuses on solving complex operational challenges by creating reliable, scalable AI systems that integrate user feedback loops and ensure high-quality model behavior across the enterprise.
Architect end-to-end Generative AI and agentic AI solutions to automate complex operational workflows.
Design and deliver multi-agent systems that decompose problems and orchestrate tasks at scale.
Translate business objectives into robust AI/ML product capabilities while ensuring security and maintainability.
Build reusable frameworks and services to standardize model development, evaluation, and deployment for other teams.
Establish production engineering rigor including observability, performance tuning, and incident readiness for AI systems.
Partner with stakeholders to identify high-value opportunities and define success metrics for enterprise transformation.
Mentor a high-performing team of AI engineers and researchers to foster technical excellence.
Drive governance for experimentation to improve model behavior through feedback loops and evaluation practices.
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 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, including reliability, monitoring, and lifecycle management.
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 with cross-functional partners.
Strong communication and stakeholder management skills to influence prioritization and align delivery to business value.
Experience deploying and operating models on Amazon Web Services platforms, including SageMaker or Bedrock (preferred).
Experience building agentic or multi-agent systems, including orchestration patterns and guardrails (preferred).
Experience establishing evaluation strategies for Generative AI systems (preferred).
Experience building reusable AI/ML platforms or shared services adopted by multiple teams (preferred).
Familiarity with modern MLOps and LLMOps practices (preferred).
Machine Learning
Deep Learning
Generative AI
LLMs
NLP
Python
Java
C++
Transformers
Hugging Face
TensorFlow
PyTorch
NumPy
Scikit-Learn
Pandas
AWS
SageMaker
Prompt Engineering
Big Data
Agentic AI
Machine Learning
Large Language Models
Reinforcement Learning
Amazon SageMaker
Amazon Bedrock
Kubernetes
Distributed Systems
Experimental Design