Software Engineer III - AI Research

About the role

Join JPMorgan Chase where you will build and ship production AI at global scale. As a Software Engineer III on JPMorgan Chase's AI/ML Data Platforms - AI Research team, you'll design Python-first platforms and GenAI apps (including agents), turn research into secure, scalable products, and automate across cloud with modern CI/CD and IaC. Partner with AIR and MLCoE to shape how AI is built and deployed across the firm.

Job Responsibilities

• Develops and writes software applications for AI/ML platforms as well as building Generative AI based applications including Agents – particularly strong in Python.
• Utilizes creative problem-solving skills to design, develop, and troubleshoot technical solutions, thinking beyond conventional approaches to innovate and resolve complex technical challenges.
• Proactively identifies opportunities to streamline, eliminate, or automate the remediation of recurring issues and developer challenges, enhancing the operational efficiency and excellence of software applications and systems.
• Works closely with Data Scientists and AI Researchers to advance experiments into more robust, scalable, highly optimized production-grade apps.
• Adds to team culture of opportunity, inclusion, and respect.
• 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.

Required Qualifications, Capabilities, And Skills

• Formal training or certification on software engineering concepts and 3+ years of applied experience.
• Practical experience in Infrastructure as Code development, ideally using Terraform.
• Hands-on practical experience in application development, testing, and ensuring operational stability.
• Advanced proficiency in one or more programming languages, with a strong focus on Python.
• Expertise automation and continuous integration, delivery, and testing (CI/CD/CT) methods.
• Comprehensive understanding of the Software Development Life Cycle (SDLC) and Model Development Life Cycle (MDLC).
• Deep understanding of agile methodologies and basic proficiency in architectural frameworks.
• Demonstrated proficiency in platform development and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, etc.).
• 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.

Preferred qualifications, capabilities, and skills

• Demonstrates initiative in learning and adapting to new technologies and methodologies, as well as demonstrable mastery of AI tools to enhance productivity and efficiency in daily tasks.
• Self-motivated and proactive, with a strong ability to identify issues and challenge the status quo.
• Proven problem-solving skills with a focus on innovation and continuous improvement.
• Experience in / exposure to a major business facing integrated application environment (e.g. risk, trading) and working with business facing developers.
• Excellent communication and collaboration skills to work effectively within cross-functional teams.