Lead Software Engineer - Java

Join us and take your software engineering career to new heights. You'll have the opportunity to lead talented engineers, shape impactful technology products, and contribute to a collaborative, inclusive team culture. At JPMorganChase, we empower you to grow your skills and make a real difference. Be part of a team where your ideas and leadership drive meaningful change. Discover the rewards of building technology that matters. Job Summary: As a Lead Software Engineer at JPMorganChase within the Finance Technology team in Corporate Technology, you will guide and support a team of engineers to deliver secure, stable, and scalable technology solutions. You will collaborate across teams and stakeholders, ensuring alignment with business objectives. You will lead technical deliverables, drive process improvements, and foster a culture of diversity, equity, and inclusion. Your leadership will help shape the future of our technology and our team's success. Job Responsibilities: Provide direction, oversight, and coaching for a team of software engineers, supporting their growth and technical development Ensure successful collaboration across teams and stakeholders, maintaining alignment with business objectives and delivery goals Lead and manage large-scale technical deliverables, driving quality outcomes from design through to production Execute software solutions across design, development, and technical troubleshooting, setting a high standard for engineering excellence Define and lead technology and process implementations to achieve firmwide objectives at regional and global scale Identify hidden problems and patterns in data, leveraging insights to drive continuous improvements across systems and processes Promote coding hygiene and system architecture enhancements, championing best practices across the team Foster a culture of diversity, equity, inclusion, and respect, creating an environment where every team member can thrive Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team 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 advanced applied experience Proven ability to manage software engineering teams delivering quality software at scale in a large corporate environment Hands-on experience in system design, application development, testing, and operational stability Proficiency in coding in one or more languages such as Java or Spark, with experience developing, debugging, and maintaining code Knowledge of modern programming and database querying languages, including SQL, relational databases, and NoSQL Solid understanding of agile methodologies, including continuous integration and delivery, application resiliency, and security Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g., cloud, AI, machine learning, mobile) Ability to solve data-oriented problems using technologies such as SQL, relational databases, Spark, and NoSQL 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: Additional formal training or certification in software engineering concepts beyond foundational level Exposure to AI tools and technologies for software development and engineering workflows Experience with Spark performance tuning for complex calculations on large datasets Experience delivering production changes to complex software using Scala and Spark If you’re ready to lead, innovate, and make an impact, we invite you to join our team and shape the future of finance technology with us.