AI/ML Engineer -Agentic Private Bank Engineer, Senior Associate

JP Morgan Chase; Jersey City (NJ); On-site; USD 150,000 - 230,000; Full time

Job summary

JP Morgan Chase is seeking an AI/ML Engineer to join the Private Bank initiative focused on agentic AI and scalable ML platforms. The role involves collaboration across Data Science, Product, and business units to build data pipelines, deploy prompt-based NLP models, and advance AI tooling within a robust production environment.

You will design and optimize data processing workflows, research prompt engineering techniques, and contribute to scalable AI services that support financial domain

Qualifications

• Formal software engineering training or cert with 3+ years of applied experience.
• Experience designing prompt-based AI/chatbot solutions.
• Strong SQL and NoSQL skills with OpenSearch/Elasticsearch/Lucene.
• Proficient Python; experience with PyTorch or TensorFlow.
• Experience building data pipelines for structured and unstructured data.
• Experience deploying NLP/LLM models via APIs in cloud.
• Familiarity with LLM orchestration and agentic AI libraries.
• Hands-on MLOps experience.

Responsibilities

• Collaborate with Data Science, Product, and business stakeholders to design, implement, and monitor robust database solutions predicated on OpenSearch.
• Design, write, and deploy Python in support of ML products and tools; deploy prompt-based models on LLMs in finance.
• Research prompt engineering techniques to improve prompt-based model performance and orchestration.
• Collaborate with cross-functional teams to identify requirements and develop solutions to meet business needs.
• Communicate effectively with technical and non-technical stakeholders.
• Build and maintain data pipelines and workflows for prompt engineering on LLMs using cloud scalability.
• Develop and maintain tools/frameworks for prompt-based model training, evaluation and optimization.
• Analyze data to evaluate model performance and identify improvements.

Skills

Python programming

Prompt design & implementation

SQL & NoSQL

Data pipelines

APIs integration

Cloud platforms

MLOps

Stakeholder communication

Tools

OpenSearch

Elasticsearch

Apache Lucene

Git

Containerization

CI/CD

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

• Collaborate with Data Science, Product, and business stakeholders to design, implement, and monitor robust database solutions predicated on OpenSearch

• Design, write, and deploy well-crafted and well-tested Python in support of Machine Learning products and tools across the company
  Design, deploy and manage prompt-based models on LLMs for various NLP tasks in the financial services domain

• 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.

• Collaborate with cross-functional teams to identify requirements and develop solutions to meet business needs within the organization

• Communicate effectively with both technical and non-technical stakeholders

• Build and maintain data pipelines and data processing workflows for prompt engineering on LLMs utilizing cloud services for scalability and efficiency.

• Develop and maintain tools and framework for prompt-based model training, evaluation and optimization

• Analyze and interpret data to evaluate model performance to identify areas of improvement

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 3+ years applied experience

• Experience with prompt design and implementation or chatbot application

• Advanced knowledge of SQL and NoSQL (OpenSearch, Elasticsearch, and / or Apache Lucene) with Git, containerization, and CI / CD

• Strong programming skills in Python with experience in PyTorch or TensorFlow

• Experience building data pipelines for both structured and unstructured data processing.

• Experience in developing APIs and integrating NLP or LLM models into software applications

• Hands-on experience with cloud platforms (AWS or Azure) for AI/ML deployment and data processing.

• Excellent problem-solving and the ability to communicate ideas and results to stakeholders and leadership in a clear and concise manner

• Basic knowledge of deployment processes, including experience with GIT and version control systems

• Familiarity with LLM orchestration and agentic AI libraries

• Hands on experience with MLOps tools and practices, ensuring seamless integration of machine learning models into production environment

Preferred qualifications, capabilities, and skills

• Familiarity with model fine-tuning techniques such as DPO and RLHF.

• Knowledge of Java, Spark

• Knowledge of financial products and services including trading, investment and risk management