Lead Software Engineer - Backend Java, Markets Tech

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, 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. As a core technical contributor, you are responsible for delivering critical technology solutions supporting the Equities Broker Dealer and Prime Finance platform, including securities lending, trade lifecycle, and clearing & settlement capabilities, in alignment with the firm's business objectives. You will also integrate AI/ML and GenAI capabilities into core platforms in a way that is secure, governable, and operable at enterprise scale.Job ResponsibilitiesExecutes creative software solutions, design, development, and technical troubleshooting with the ability to solve complex problems and deliver scalable solutions across distributed systems and microservices architecturesDevelops secure, high-quality production code, and reviews and debugs code written by others to ensure engineering excellenceBuild and integrate AI/ML and GenAI into production platforms—LLMs, RAG, embeddings, vector databases, and MLOps for lifecycle management, monitoring, and governance.Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability, resiliency, and performance of applicationsDrives architecture and design decisions influencing system scalability, performance, and long-term platform evolutionLeads evaluation sessions with internal teams and stakeholders to assess architectural designs and ensure alignment with enterprise technology strategiesContributes to platform modernization through adoption of cloud-native, event-driven, and microservices-based architecturesPartners with business, product, and operations teams to translate Prime Finance and Broker Dealer requirements into scalable technical solutionsEnsures robust delivery across environments with strong focus on SDLC, testing (unit, SIT, UAT), and production stabilityDrives 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 skillsFormal training or certification on software engineering concepts and 5+ years of applied experienceHands-on practical experience delivering system design, application development, testing, and operational stability in large-scale enterprise environmentsAdvanced proficiency in Java, Spring Boot and REST APIs programming language within microservices in a distributed systems architectureStrong experience with Relational databases (Oracle/DB2) and/or NoSQL (MongoDB) and CI/CD pipelines, DevOps, and automation practicesProficient in all aspects of the Software Development Life Cycle (SDLC)Strong problem-solving, analytical, and stakeholder communication skillsDemonstrated proficiency in building high-volume, low-latency, mission-critical financial systemsHands-on experience integrating AI/ML and GenAI into enterprise applications, including LLMs, RAG pipelines, embeddings, vector stores/databases, model evaluation, and production monitoring (MLOps).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 practicesPractical experience working across cross-functional teams in complex enterprise organizationsPreferred qualifications, skills, and capabilitiesCloud-native development (AWS or equivalent)Exposure to Prime Finance, Securities Lending, or Broker Dealer platformsExperience with event-driven architectures (Kafka, MQ) and messaging systemsFamiliarity with modern front-end technologies (React, UI frameworks)Exposure to domain-driven design, full-stack development, and modern architectural patternsExperience with observability tools (Splunk, Grafana, Prometheus, ELK)Interest in adopting emerging technologies (AI-assisted development, automation, advanced analytics) JPMorgan Chase