GenAI/ML VP Engineer - AI Platform Lead

JPMorgan Chase; Plano (TX); On-site; USD 230,000 - 320,000; Full time

Job summary

JPMorgan Chase is seeking a Vice President-level Machine Learning Engineer focused on GenAI/ML to design, build, and maintain an AI operations platform for Home Lending Technology. The role requires deep AI/ML and infrastructure expertise to deliver scalable, secure AI systems.

You will lead generative AI initiatives, craft production-grade code in Python/Java, and leverage React/Angular to create user-friendly AI interfaces, while applying CI/CD and security best practices across projects.

Qualifications

• 7+ years of strong proficiency in Python or Java and ability to architect AI models from scratch.
• 2+ years of generative AI development and prompt engineering.
• Experience in system design, app development, testing, and AI project operations.
• 5+ years of React or Angular experience.
• 2+ years of AWS experience.
• Familiarity with CI/CD, resiliency, and security in AI projects.
• Experience with LLM models and agentic tools.

Responsibilities

• Lead design, development, and deployment of generative AI solutions aligned with business goals and technical requirements.
• Demonstrate expertise in generative AI and evaluate new methods to boost AI capabilities.
• Architect and deliver production-grade code in Python/Java, focusing on security and quality.
• Create intuitive UIs for AI apps using React or Angular and perform code reviews.

Skills

Python

Java

Generative AI

Prompt Engineering

React

Angular

AWS

Tools

TensorFlow

PyTorch

Scikit-learn

Keras

Job description

JPMorgan Chase is seeking a Vice President-level Machine Learning Engineer focused on GenAI/ML to design, build, and maintain an AI operations platform for Home Lending Technology. The role requires deep AI/ML and infrastructure expertise to deliver scalable, secure AI systems.

You will lead generative AI initiatives, craft production-grade code in Python/Java, and leverage React/Angular to create user-friendly AI interfaces, while applying CI/CD and security best practices across projects.