AI Platform Engineer – GenAI & Production AI

Testing Site - JPMC; Jersey City (NJ); On-site; USD 130,000 - 200,000; Full time

Job summary

JPMorgan Chase is seeking a Software Engineer III to design Python-driven AI/ML platforms and GenAI apps for production use. You will develop secure, scalable solutions and automate deployments across cloud environments using modern CI/CD practices and Infrastructure as Code.

You will work with AIR and MLCoE to translate research into robust, production-grade software, partnering with Data Scientists and AI Researchers to advance experiments toward scalable outcomes.

Qualifications

• Formal training or certification in software engineering concepts
• 3+ years of applied software engineering experience
• Hands-on experience with software development, testing, and operational stability
• Advanced proficiency in Python and related tooling
• Experience with CI/CD/CT and automation practices

Responsibilities

• Develops and writes software applications for AI/ML platforms and AI-based applications including agents, with strong Python focus
• Applies creative problem-solving to design, develop, and troubleshoot solutions
• Explores agent-based programming and latest techniques for production readiness
• Streamlines remediation of recurring issues to improve reliability and efficiency
• Uses CI/CD to deliver cloud platforms and supports experimentation environments (e.g., Jupyter)
• Collaborates with Data Scientists and AI Researchers to productionize experiments
• Contributes to a culture of opportunity, inclusion, and respect

Skills

Python

CI/CD

Agile methodologies

SDLC/MDLC

Automation

Education

Formal software engineering training or certification

Tools

Terraform

Job description

JPMorgan Chase is seeking a Software Engineer III to design Python-driven AI/ML platforms and GenAI apps for production use. You will develop secure, scalable solutions and automate deployments across cloud environments using modern CI/CD practices and Infrastructure as Code.

You will work with AIR and MLCoE to translate research into robust, production-grade software, partnering with Data Scientists and AI Researchers to advance experiments toward scalable outcomes.