Create secure, high-quality production code and conduct code reviews and debugging for code written by others
Troubleshoot complex technical problems and implement creative software solutions beyond routine approaches
Maintain algorithms and services that integrate with dependent systems reliably and efficiently
Identify hidden problems and patterns in data to drive improvements to coding hygiene and system architecture
Provide technical guidance and direction to support the business and partner technical teams
Contribute to an agile team environment with a focus on secure and resilient delivery
Promote a team culture of diversity, opportunity, inclusion, and respect
Required Qualifications, Capabilities, and Skills
Proficiency in Python and at least one additional modern programming language (for example Golang or TypeScript)
Experience building and supporting production software in a large enterprise environment
Experience designing, developing, and maintaining APIs and backend services, including concurrency concepts
Experience creating secure, high-quality code, including reviewing and debugging code written by others
Experience with continuous integration and continuous delivery practices
Experience applying security and resiliency practices in software delivery
Experience building or supporting data pipelines for analytics, model evaluation, and training with appropriate controls (for example versioning and validation)
Experience with large language model application patterns, including retrieval-augmented generation and prompt design
Preferred Qualifications, Capabilities, and Skills
Experience delivering AI or machine learning products end to end, from development through deployment and ongoing support
Experience partnering closely with research scientists and data engineers to productionize models and workflows
Applied Innovation of AI is a machine learning team within the Chief Data and Analytics Office Technology group at JPMorganChase. The team tackles business-critical priorities using innovative machine learning techniques, with a focus on machine learning for software, cybersecurity, and technology infrastructure. The team partners across lines of business and engineering groups to deliver long-term initiatives that support firm growth.
