
AI/ML Engineer -Agentic Private Bank Engineer, Senior Associate
Jersey City, NJFull-time$138–195K/yrSeen 3 days agoSeen in employer's feed 3 days ago
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Job overview
The AI/ML Engineer will help develop an Agentic Private Bank by researching, building, and productionizing machine-learning models, services, and platforms. The role collaborates with business and technical stakeholders to deliver software solutions, build scalable data pipelines, and improve prompt-based models and tools. It focuses on LLMs, agentic AI, and financial-services applications, with work spanning model development, deployment, evaluation, and optimization.
Skills & qualifications
Skills
Qualifications
Benefits
Full job description
AI/ML Engineer -Agentic Private Bank Engineer, Senior Associate
Jersey City, NJ, United States
Job Information
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Job Identification 210797991
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Job Category Predictive Science
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Business Unit Asset & Wealth Management
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Posting Date 10/30/2026, 06:03 PM
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Locations 575 Washington Blvd, Jersey City, NJ, 07310, US
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Job Schedule Full time
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Job Shift Day
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Base Pay/Salary Jersey City,NJ $137,750.00-$195,000.00
Job Description
This is a rare opportunity to help shape the future of our Private Bank. With the sponsorship from the CEO and the heads of the business, our goal is to create an Agentic Private Bank - reimagining the entire process from start to finish, rethinking the operating model including organizational structures and developing AI agents equipped with the latest tools and technologies to fundamentally reshape how we perform this business.
As an AI ML Engineer within the team at JPMorgan, you will collaborate with all lines of business and functions to deliver software solutions. You will have opportunity to research, experiment, develop, and productionize high-quality machine learning models, services, and platforms to make a significant business impact. You will also design and implement highly scalable and reliable data processing pipelines and perform analysis and insights to promote and optimize business results.
Job responsibilities
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Collaborate with Data Science, Product, and business stakeholders to design, implement, and monitor robust database solutions predicated on OpenSearch
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Design, write, and deploy well-crafted and well-tested Python in support of Machine Learning products and tools across the companyDesign, deploy and manage prompt-based models on LLMs for various NLP tasks in the financial services domain
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Conduct research on prompt engineering techniques to improve the performance of prompt-based models within the financial services field, exploring and utilizing LLM orchestration and agentic AI libraries.
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Collaborate with cross-functional teams to identify requirements and develop solutions to meet business needs within the organization
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Communicate effectively with both technical and non-technical stakeholders
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Build and maintain data pipelines and data processing workflows for prompt engineering on LLMs utilizing cloud services for scalability and efficiency.
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Develop and maintain tools and framework for prompt-based model training, evaluation and optimization
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Analyze and interpret data to evaluate model performance to identify areas of improvement
Required qualifications, capabilities, and skills
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Formal training or certification on software engineering concepts and 3+ years applied experience
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Experience with prompt design and implementation or chatbot application
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Advanced knowledge of SQL and NoSQL (OpenSearch, Elasticsearch, and / or Apache Lucene) with Git, containerization, and CI / CD
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Strong programming skills in Python with experience in PyTorch or TensorFlow
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Experience building data pipelines for both structured and unstructured data processing.
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Experience in developing APIs and integrating NLP or LLM models into software applications
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Hands-on experience with cloud platforms (AWS or Azure) for AI/ML deployment and data processing.
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Excellent problem-solving and the ability to communicate ideas and results to stakeholders and leadership in a clear and concise manner
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Basic knowledge of deployment processes, including experience with GIT and version control systems
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Familiarity with LLM orchestration and agentic AI libraries
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Hands on experience with MLOps tools and practices, ensuring seamless integration of machine learning models into production environment
Preferred qualifications, capabilities, and skills
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Familiarity with model fine-tuning techniques such as DPO and RLHF.
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Knowledge of Java, Spark
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Knowledge of financial products and services including trading, investment and risk management
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 (https://careers.jpmorgan.com/us/en/how-we-hire/faqs) for more information about requesting an accommodation.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
About the Team
J.P. Morgan Asset & Wealth Management delivers industry-leading investment management and private banking solutions. Asset Management provides individuals, advisors and institutions with strategies and expertise that span the full spectrum of asset classes through our global network of investment professionals. Wealth Management helps individuals, families and foundations take a more intentional approach to their wealth or finances to better define, focus and realize their goals.
How this job compares
Set against the 562 open AI/ML Engineer jobs on Olive Jobs, counted November 3, 2026.
- Pay
- This posting$138–195K/yr
- US median$117–210K/yr434 salary ranges
This range's midpoint, $166K, is close to the US median midpoint ($166K) — in the middle half of AI/ML Engineer salary ranges across the US.
- Openings
- Olive Jobs lists 17 open AI/ML Engineer jobs in New Jersey and 562 across the US. 6% of them nationwide are listed as remote or flexible.
- Hiring the most across the US
- Accenture72 open
- Cardinal Health53 open
- SMX53 open
- Experience
- This posting asks for at least 3 years of experience — less than three in four AI/ML Engineer postings that state a minimum ask for (median 5 years, across 518 postings).
- Education
- 253 of the 562 open AI/ML Engineer jobs (45%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on November 3, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
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