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About This Role
JOB DESCRIPTION
Join a high\-impact team at the forefront of AI innovation within Chase Wealth Management. As a recognized leader in AI transformation and strategic execution, you will drive meaningful change, influence senior management, and shape the future direction of our business. This is an opportunity to lead industry\-defining initiatives, collaborating across product, technology, and operations teams, and delivering solutions that set new standards for our advisors and clients.
As a AI Transformation \& Strategic Execution Lead, in Chase Wealth Management, you will be responsible for developing, driving, and owning a comprehensive AI strategy. You will serve as a trusted advisor to senior leaders, translating complex data and competing priorities into compelling, data\-driven narratives that drive alignment, secure buy\-in, and inspire action. Operating in a highly matrixed environment, you will architect a dynamic portfolio of AI initiatives, challenge the status quo, and uncover ambitious, high\-impact opportunities that deliver measurable outcomes and best\-in\-class experiences for our clients and advisors.
Your leadership will ensure that AI initiatives are visionary, value\-driven, and aligned with business goals. You will foster a culture of innovation, responsible AI adoption, and data\-driven decision\-making, while orchestrating complex, cross\-functional change initiatives across the organization. While you will not directly lead a team, you will influence and help manage the AI agenda in partnership with various teams across the business.
Job Responsibilities
- Develop, drive, and own a comprehensive AI strategy for Chase Wealth Management, aligned to business goals and growth objectives
- Architect and spearhead the AI portfolio, shifting from traditional management to a dynamic value\-creation engine focused on measurable business impact
- Identify, prioritize, and champion high\-impact AI use cases to improve operational efficiency, advisor productivity, and client service
- Influence and help manage the AI agenda with cross\-functional teams across technology, digital, product, and operations in a matrixed organization, often through indirect management and collaboration
- Partner with Product and Technology teams to design, build, and integrate AI solutions, serving as a subject matter expert and thought leader on emerging AI trends and best practices
- Translate portfolio data into powerful, data\-driven narratives and actionable insights for executive leadership, focusing on ROI, strategic alignment, and business impact
- Develop and deploy robust analytical frameworks and governance models to rigorously assess, prioritize, and measure the success of all AI initiatives from intake to scaling
- Collaborate with advisors and field leaders to translate needs into actionable AI initiatives
- Champion best practices in strategic planning, change management, and benefits realization across the organization
- Monitor and evaluate the effectiveness of AI solutions, providing insights and recommendations for continuous improvement
- Forge strategic partnerships across all Lines of Business, driving alignment on ambitious goals and orchestrating complex, cross\-functional change initiatives
Required Qualifications, Capabilities, and Skills
- Bachelor's degree required
- 10\+ years of proven experience in AI leadership, strategy, and solution design within financial services, wealth management, management consulting, or strategic program management
- Demonstrated track record of leading large\-scale business transformation initiatives and delivering impactful AI use cases in complex business environments
- Hands\-on experience building and implementing AI\-driven solutions, with expertise in Generative AI, agentic AI, machine learning, and automation technologies
- Deep subject matter expertise in AI/ML concepts and their practical application to solve real\-world business challenges and drive value
- Hypothesis\-driven problem solver with the ability to dissect complex, ambiguous problems and architect elegant, data\-driven solutions
- Mastery of executive\-level communication; able to distill complex analyses into simple, compelling narratives and build sophisticated analytical models to support recommendations
- Demonstrated experience partnering with technical teams to deliver solutions from concept to implementation, and ability to work cross\-functionally as an individual contributor
- Exceptional influencing and relationship\-building skills, with the ability to build trust and consensus with senior executives, cross\-functional partners, and technical teams
- Strategic vision to drive transformation and break down silos across teams
- Familiarity with competitor AI strategies, industry best practices, and responsible AI adoption and governance
Preferred Qualifications, Capabilities, and Skills
- Experience building AI roadmaps with measurable business outcomes
- Experience with data visualization tools (e.g., Tableau, Alteryx) is a strong plus
- Background in technology, product, analytics, consulting, or digital transformation
- Wealth management experience is preferred but not required
- Experience designing and executing holistic AI strategies across multiple business units
- Ability to operate effectively in a matrixed organization, leading through influence and indirect management
- A bias for action and an entrepreneurial spirit; comfortable challenging the status quo and relentlessly driving outcomes
ABOUT US
Chase is a leading financial services firm, helping nearly half of America's households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs.
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission\-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on\-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
Equal Opportunity Employer/Disability/Veterans
ABOUT THE TEAM
Our Consumer \& Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We're proud to lead the U.S. in credit card sales and deposit growth and have the most\-used digital solutions – all while ranking first in customer satisfaction.
We are here to help you manage your money with checking, savings and credit cards, combining the latest banking technology with comprehensive solutions to meet the financial needs of nearly half of U.S. households.
Salary Context
This $183K-$294K range is above the 75th percentile for AI/ML Engineer roles in our dataset (median: $175K across 2162 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 4,317 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At JPMorganChase, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $214,900 based on 6,420 positions with disclosed compensation. Director-level AI roles across all categories have a median of $274,554. This role's midpoint ($238K) sits 11% above the category median. Disclosed range: $183K to $294K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
JPMorganChase AI Hiring
JPMorganChase has 141 open AI roles right now. They're hiring across AI Software Engineer, AI/ML Engineer, Data Scientist, AI Product Manager. Positions span Jersey City, NJ, US, New York, NY, US, Seattle, WA, US. Compensation range: $120K - $450K.
Location Context
AI roles in New York pay a median of $220,000 across 1,650 tracked positions.
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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