VP AI/ML Lead Engineer - Production ML Architect

Next Frontier Capital; Wilmington (DE); On-site; USD 180,000 - 240,000; Full time

Job summary

JPMorgan Chase & Co. is seeking an AI Engineering Lead Engineer Vice President to drive hands-on development of AI/ML solutions for Private Bank clients. You will lead architecture, data pipelines, and production deployments on AWS/Azure.

The role requires expert Python, ML theory, and strong leadership to collaborate with global teams and translate business needs into scalable AI platforms.

Qualifications

• MS in Computer Science, Statistics, Mathematics, or Machine Learning and minimum 7 years of development experience, with at least 4 years on AI.
• Experience using LLMs (OpenAI, Anthropic, or others) to solve business problems.
• Strong Python programming and knowledge of data structures, algorithms, ML, data mining, IR, and statistics.
• Independent end-to-end solution design with focus on modern architecture, scalability, and security.
• Knowledge of data management, data model design, and real-time processing on SQL and NoSQL stores.
• Proven leadership and ability to communicate with senior technical and business partners.

Responsibilities

• Collaborate with firmwide AI/ML teams and partners to drive alignment and adoption of AI capabilities.
• Hands-on architecture and implementation of lighthouse ML and LLM-powered solutions.
• Design and deploy scalable data processing pipelines and model inference services.
• Experiment, develop, and productionize ML models and services with impact.
• Deploy solutions into public cloud infrastructure.

Skills

Python

LLMs

Data analysis

Distributed systems

Communication

Leadership

Education

MS in Computer Science/Statistics/Math/ML

Tools

AWS

Azure

PostgreSQL

OpenSearch

Redis

Kubernetes

Next.js

Svelte

Job description

JPMorgan Chase & Co. is seeking an AI Engineering Lead Engineer Vice President to drive hands-on development of AI/ML solutions for Private Bank clients. You will lead architecture, data pipelines, and production deployments on AWS/Azure.

The role requires expert Python, ML theory, and strong leadership to collaborate with global teams and translate business needs into scalable AI platforms.