Senior Applied AI/ML Engineer – Scalable, Secure Systems

Aumni; Jersey City (NJ); On-site; USD 120,000 - 170,000; Full time

Job summary

JPMorganChase is seeking a Software Engineer III to join the Asset & Wealth Management team in Jersey City, NJ. You will design and deliver trusted market-leading technology products in a secure, scalable way within an agile environment.

Responsibilities include building production-grade code, applying AI coding tools, and ensuring robust architecture while working with large data sets to drive continuous improvement.

Qualifications

• Formal training or certification on software engineering concepts and 3+ years applied experience in applied AI/ML engineering.
• Hands-on practical experience in system design, application development, testing, and operational stability.
• Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages.
• Strong programming skills in Python, expertise in using AI code assist tools such as Claude Code, OpenAI and with experience in developing and maintaining production-level code.
• Proficiency in working with large datasets and data science.
• Solid understanding of AI/ML algorithms and techniques, AI agent usage, and overall natural language processing.
• Experience with cloud platforms, such as AWS for deploying and scaling AI/ML models.
• Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
• Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.
• Overall knowledge of the Software Development Life Cycle
• Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security

Responsibilities

• Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build agentic solutions or breakdown technical problems
• Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
• Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
• Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
• Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
• Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture

Skills

Python

AI/ML

AWS

CI/CD

Data analysis

Secure coding

Production code

Tools

Claude Code

OpenAI

Job description

JPMorganChase is seeking a Software Engineer III to join the Asset & Wealth Management team in Jersey City, NJ. You will design and deliver trusted market-leading technology products in a secure, scalable way within an agile environment.

Responsibilities include building production-grade code, applying AI coding tools, and ensuring robust architecture while working with large data sets to drive continuous improvement.