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AI Engineering tackle business critical priorities using innovative machine learning techniques and technologies with a focus on machine learning for Software, Cybersecurity and Technology Infrastructure. The team partners closely with all lines of business and engineering teams across the firm to execute long-term projects in these areas that require significant machine learning development to support JPMC businesses as they grow.\nAs a Principal Software Engineer at JPMorganChase within CDAO Technology Group in the Applied Innovation (of AI) Engineering team, you will design, develop, deploy, and maintain advanced AI products. You’ll collaborate with software engineers, data engineers, and data scientists to deliver trusted solutions. Your role is central to executing long-term projects that drive innovation and support our business growth. You’ll contribute to a culture of inclusion and technical excellence.\nJob Responsibilities\nCollaborates with engineers, data scientists, and product owners, to deliver products to production.\nBuilds and maintain data pipelines for analytics, model evaluation, and training (includes versioning, compliance and validation).\nExecutes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems\nProvides feedback and proposes improvements to architecture governance practices\nCreates secure and high-quality production code, and reviews and debugs code written by others. Maintains algorithms that run synchronously with appropriate systems\nProactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture\nRegularly provides technical guidance and direction to support the business and its technical teams and vendors\nArchitects and governs agentic AI-enabled engineering workflows (using enterprise-authorized tools within the work environment) to improve delivery speed, code quality, and operational outcomes at scale (e.g., AI-driven PR review assistance, test generation/maintenance, release readiness checks, incident triage and root-cause acceleration), while defining guardrails for validation, security, resiliency, and reuse across teams\nApplies 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 at scale\nRequired Qualifications, Capabilities and Skills\nProven programming/scripting skills with multiple modern programming languages including Python, Golang, TypeScript and similar technologies in an AWS /Cloud environment\nExperience in the use of GPT, LLM, RAG, Gen AI, Prompt Engineering related technologies\nExperience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages\nCurrent experience of agile methodologies such as CI/CD, Applicant Resiliency, and Security\nSolid understanding of software applications and technical processes within a related technical discipline (e.g. Synchronous and non-synchronous APIs, Concurrency, etc.)\nCreates complex and scalable coding solutions using appropriate software design 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