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About This Role
JOB DESCRIPTION
Join the HR Vendor Management team for an exciting role managing risks related to AI/ML, maintaining vendor risk governance, driving solutions, and leading vendor selection and implementation.
As a Vice President in the HR Vendor Management Team, you will oversee and enhance vendor risk management and governance practices. You will focus on managing risks related to Artificial Intelligence and Machine Learning (AI/ML), leading vendor selection and renewal for high-value and high-risk engagements, and strengthening cyber and information security oversight. You will drive strategic initiatives, collaborate with global teams, and ensure the vendor portfolio aligns with organizational goals and industry standards.
Job Responsibilities
- Oversee vendor selection, onboarding, renewal, and rationalization for high-value and high-risk engagements, ensuring alignment with business goals, risk appetite, cost-effectiveness, and alignment with tech-echo systems.
- Lead and enhance vendor risk governance frameworks, with a focus on AI/ML, cyber, and information security risks, in partnership with cross-functional teams.
- Lead implementation and improvement of vendor value and AI/ML risk governance in partnership with teams like Controls, Data, Legal, Technology.
- Maintain SOPs, playbooks, and best practices for vendor risk, renewals, and AI/ML governance.
- Establish and monitor KPIs and metrics for vendor performance, risk exposure, and mitigation effectiveness.
- Lead cross-functional teams in risk reviews, governance routines, and process improvements.
- Prepare and deliver reports and presentations on vendor risk and performance to senior management.
- Foster strong relationships with internal partners (HR, Controls, Tech, Legal, Finance) to resolve issues and drive improvement.
- Drive assessment and mitigation of cyber risks in vendor engagements, partnering with technology, risk, and compliance teams.
- Enable Delivery Manager with onboarding project execution, providing leadership visibility of progress
- Stay current on industry trends, regulatory developments, and emerging technologies in vendor risk, AI/ML, and cyber risk; recommend process enhancements.
Required qualifications, capabilities and skills
- Bachelor's degree
- 7+ years of progressive experience in project management, risk management, or a related discipline, with a track record of leading high-impact initiatives and cross-functional teams.
- Deep understanding of vendor risk governance, including AI/ML risk management, cyber risk, and complex contract evaluation and renewal processes for high-value engagements.
- Demonstrated ability to analyze complex business challenges, develop innovative solutions, and drive strategic change in a dynamic environment.
- Outstanding written and verbal communication skills, with the ability to influence, negotiate, and present to senior leadership and diverse stakeholder groups.
- Experience designing, implementing, and optimizing processes, SOPs, and metrics to ensure operational rigor, compliance, and continuous improvement.
- Familiarity with emerging technologies, data analytics, and automation tools to enhance vendor risk management and reporting.
- Strong collaboration skills, with the ability to build trusted relationships across HR, Technology, Legal, Compliance, and Finance teams.
- Proven ability to manage multiple priorities, deliver results under pressure, and adapt to evolving business needs and regulatory requirements.
- High ethical standards and sound judgment in handling sensitive information, risk decisions, and confidential vendor relationships.
Preferred qualifications, capabilities and skills
- Master’s degree in Business Administration, Risk Management, Information Technology, or a related field.
- Professional certifications such as Certified Third Party Risk Professional (CTPRP), Project Management Professional (PMP), Certified Information Systems Security Professional (CISSP), or similar credentials.
- Demonstrated experience in driving process automation, digital transformation, or leveraging advanced analytics to enhance vendor risk management and operational efficiency.
- In-depth knowledge of regulatory frameworks and industry standards governing vendor risk, AI/ML, and cyber risk in financial services or highly regulated environments.
- Proven success in leading organizational change, influencing culture, and implementing best practices across large, complex organizations.
- Experience managing vendor risk and governance across multiple geographies, cultures, and regulatory jurisdictions.
- Track record of contributing to industry forums, publishing insights, or presenting at conferences on vendor risk, AI/ML governance, or cyber risk topics.
Additional Information
- *This role requires the ability to physically work in either our New York, NY or Jersey City, NJ , Columbus, OH and Plano, TX offices 5 days a week*
- *Applicants must be authorized to work for any employer in the U.S. We are unable to provide immigration sponsorship or take over sponsorship of an employment/work visa at this time (including but not limited to H1B, H4 – EAD, OPT, TN, or L visas)*
- *Final Job Grade level and corporate title will be determined at time of offer and may differ from this posting*
- *This role does not provide relocation assistance so all candidates must be local to the work locations listed in the job posting or willing to relocate on their own immediately upon hiring*
ABOUT US
JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.
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.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
ABOUT THE TEAM
Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we’re setting our businesses, clients, customers and employees up for success.
Global Finance & Business Management works to strategically manage capital, drive growth and efficiencies, maintain financial reporting and proactively manage risk. By providing information, analysis and recommendations to improve results and drive decisions, teams ensure the company can navigate all types of market conditions while protecting our fortress balance sheet.
Salary Context
This $128K-$210K range is below the median for AI/ML Engineer roles in our dataset (median: $170K across 217 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 37,339 AI roles we're tracking, AI/ML Engineer positions make up 91% 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 $154,000 based on 8,743 positions with disclosed compensation. This role's midpoint ($169K) sits 10% above the category median. Disclosed range: $128K to $210K.
Across all AI roles, the market median is $190,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $300,688. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $85,000; Mid: $147,000; Senior: $225,000; Director: $230,600; VP: $248,357.
JPMorganChase AI Hiring
JPMorganChase has 7 open AI roles right now. They're hiring across AI/ML Engineer, AI Product Manager. Positions span New York, NY, US, Columbus, OH, US, Palo Alto, CA, US. Compensation range: $165K - $260K.
Location Context
AI roles in New York pay a median of $204,100 across 1,633 tracked positions. That's 7% above the national median.
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 37,339 open positions tracked in our dataset. By seniority: 3,672 entry-level, 23,272 mid-level, 7,048 senior, and 3,347 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (2,732 positions). The remaining 34,484 roles require on-site or hybrid attendance.
The market median for AI roles is $190,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $300,688. Highest-paying categories: AI Engineering Manager ($293,500 median, 21 roles); AI Safety ($274,200 median, 24 roles); Research Engineer ($260,000 median, 264 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 37,339 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (33,926), AI Software Engineer (823), AI Product Manager (805). 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 (3,672) are outnumbered by mid-level (23,272) and senior (7,048) 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 3,347 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (2,732 positions), with 34,484 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 $190,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $300,688. 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 Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $145,600. 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: Rag (23,721 postings), Aws (12,486 postings), Rust (10,785 postings), Python (5,564 postings), Azure (3,616 postings), Gcp (3,032 postings), Prompt Engineering (2,112 postings), Kubernetes (1,713 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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