Software Engineer

Lead Software EngineerBe an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.As a Lead Software Engineer at JPMorgan Chase within the Corporate Technology, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.Job ResponsibilitiesDesign and implement enterprise-grade Machine Learning platforms capable of deploying and running predictive models at scale.Develop web applications using service-oriented and microservices architecture with Java and Python frameworks.Integrate solutions with AWS Cloud Services, including compute, storage, databases, and security components.Build tools and automation solutions for monitoring, provisioning, and streamlining processes, services, and reporting.Establish comprehensive monitoring and alerting frameworks to ensure optimal performance, scalability, availability, and reliability.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.Partner closely with Product teams to design, build, and deliver capabilities through agile sprints.Leverage strong operational insights to recommend improvements to upstream products, processes, and policies that enhance the user experience.Utilize AI agents and emerging technologies to build prototypes for demonstration purposes, presenting to peer groups, business partners, and senior leadership.Deliver high-quality results within tight deadlines while maintaining a strong focus on code optimization, performance tuning, and engineering best practices.Required Qualifications, Capabilities, and SkillsFormal training or certification on software engineering concepts and 5+ years applied experience.Experience in building high-volume, low-latency, high-throughput transactional systems.Experience in building microservices using Java/Spring Boot and Python/Fastapi/FlaskExperience with AWS services - S3, DynamoDB, ECS, EKS, RDS, Lambda, and ALB/NLB.Experienced with pair programming agents such as GitHub Copilot/Claude code to accelerate prototyping.Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practicesStrong knowledge of RDBMS, schema design, SQL, query optimization, indexing, joins, and JDBC.Agile Development experience with SCRUM or similar methodologies?Completed AWS Developer or Solution Architect Certification?Excellent problem-solving skills and the ability to think critically and creativelyPreferred Qualifications, Capabilities, and SkillsExperience in MLOps and building model serving applicationsExperience with artificial intelligence and machine learning tools and framework in development.?Certification in DatabricksExperience in observability and production management tools (ex. Splunk / Dynatrace / Grafana)?