Principal Software Engineer

Role Overview: As a Principal Software Engineering at JPMorgan Chase within the Chief Data and Analytics Organization, you will be a key member of an agile team responsible for enhancing, building, and delivering trusted market-leading technology products. Your expertise will be crucial in evolving firm-wide Data Mesh, AI/ML, GenAI, and Data Governance platforms. You will drive advanced technical capabilities and collaborate with colleagues to deliver a scalable, high-performance platform. Key Responsibilities: - Define the technical vision and architectural direction for back-end services - Provide technical leadership through hands-on contribution, mentoring, and code reviews - Lead critical design decisions, resolve engineering obstacles, and maintain libraries, SDKs, and frameworks - Drive reliability, performance, and cost efficiency across services, embedding security and compliance considerations - Shape the technology roadmap by evaluating emerging tools and techniques - Utilize AI and coding-assist tools for improved code quality and team productivity - Partner with Product and Engineering leadership to align technical strategy with business objectives - Architect and govern agentic AI-enabled engineering workflows for improved delivery speed and operational outcomes - Apply knowledge of tools within the Software Development Life Cycle toolchain to improve automation at scale Qualifications Required: - 12+ years of engineering experience, with 5+ years at staff/principal level - Expert-level proficiency in Java 17+ and OOP/OOD - Understanding of RESTful architecture, modern front-end architectures, and multiple architectural paradigms - Proven track record in designing large-scale distributed systems and microservices architectures - Proficiency with AWS and cloud-native architecture, databases at scale, and streaming/messaging platforms - Strong understanding of QA and test automation strategies - Experience in designing and leading adoption of agentic AI-enabled development practices - Understanding of responsible AI use and control expectations in engineering workflows (Note: The JD does not contain any additional details about the company) Role Overview: As a Principal Software Engineering at JPMorgan Chase within the Chief Data and Analytics Organization, you will be a key member of an agile team responsible for enhancing, building, and delivering trusted market-leading technology products. Your expertise will be crucial in evolving firm-wide Data Mesh, AI/ML, GenAI, and Data Governance platforms. You will drive advanced technical capabilities and collaborate with colleagues to deliver a scalable, high-performance platform. Key Responsibilities: - Define the technical vision and architectural direction for back-end services - Provide technical leadership through hands-on contribution, mentoring, and code reviews - Lead critical design decisions, resolve engineering obstacles, and maintain libraries, SDKs, and frameworks - Drive reliability, performance, and cost efficiency across services, embedding security and compliance considerations - Shape the technology roadmap by evaluating emerging tools and techniques - Utilize AI and coding-assist tools for improved code quality and team productivity - Partner with Product and Engineering leadership to align technical strategy with business objectives - Architect and govern agentic AI-enabled engineering workflows for improved delivery speed and operational outcomes - Apply knowledge of tools within the Software Development Life Cycle toolchain to improve automation at scale Qualifications Required: - 12+ years of engineering experience, with 5+ years at staff/principal level - Expert-level proficiency in Java 17+ and OOP/OOD - Understanding of RESTful architecture, modern front-end architectures, and multiple architectural paradigms - Proven track record in designing large-scale distributed systems and microservices architectures - Proficiency with AWS and cloud-native architecture, databases at scale, and streaming/messaging platforms - Strong understanding of QA and test automation strategies - Experience in designing and leading adoption of agentic AI-enabled development practices - Understanding of responsible AI use and control expectations in engineering workflows (Note: The JD does not contain any additional details about the company)