Ai/ml Engineer – Agentic Private Bank Engineer , Vice President

JPMorgan Chase JPMorgan Chase · Banking · Jersey City, NJ +1 · Asset & Wealth Management

Lead the development and implementation of GenAI and Agentic AI solutions using Python to enhance automation and decision-making processes within JPMorgan Chase's Private Bank. This role involves designing, deploying, and managing prompt-based models on LLMs, conducting research on prompt engineering, and building data pipelines and evaluation frameworks for these models on cloud platforms.

What you'd actually do

  1. Lead the development and implementation of GenAI and Agentic AI solutions using Python to enhance automation and decision-making processes.
  2. Oversee the design, deployment, and management of prompt-based models on LLMs for various NLP tasks in the financial services domain.
  3. Conduct and guide 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.
  4. Collaborate with cross-functional teams to identify requirements and develop solutions to meet business needs within the organization.
  5. Communicate effectively with both technical and non-technical stakeholders, including senior leadership.

Skills

Required

  • PhD in a quantitative discipline, e.g. Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science Or an MS with at least 7 years of industry or research experience in the field.
  • Hands-on experience in building Agentic AI solutions.
  • Familiarity with LLM orchestration and agentic AI libraries.
  • 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 skills 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.
  • Hands-on experience with MLOps tools and practices, ensuring seamless integration of machine learning models into production environments.

Nice to have

  • Familiarity with model fine-tuning techniques.
  • Knowledge of financial products and services, including trading, investment, and risk management.

What the JD emphasized

  • Agentic Private Bank
  • AI agents
  • autonomous AI agents
  • Agentic AI solutions
  • agentic AI libraries

Other signals

  • AI agents
  • LLM orchestration
  • prompt engineering
  • Python
  • PyTorch or TensorFlow
  • cloud platforms