JPMorgan Chase—Lead Software Engineer – Java Low Latency

Job description

Description: We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible. As a Lead Software Engineer at JPMorganChase within the Commercial & Investment Bank, 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 conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives. Job responsibilities - Designs and develops robust, high-performance, latency-sensitive code; incorporates security requirements; and reviews code written by team members using software engineering best practices. - Writes secure, high-quality code and automated tests. - Works closely with Product Owners, Solutions Analysts, Technical Architects, and Senior Engineers to define the best technical design and development approach. - Translates business requirements into technical solutions, recommends alternative technical and business approaches, and leads engineering efforts to meet ambitious timelines with optimal solutions. - Helps refine the technical aspects of epics in collaboration with Solutions Analysts. - Produces architecture and design artifacts for complex applications while ensuring design constraints are met by code. - Drives architectural reviews, code reviews, and business demos. - Assesses compliance, risks, and vulnerabilities to ensure all systems and baselines are operationally sound, performant at scale, and exceed customer expectations. - 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. - Contributes to the ongoing development of the team, including recruitment, paired programming, peer review, and mentoring. Required qualifications, capabilities, and skills - Formal training or certification on software engineering concepts and 5+ years applied experience - Excellent understanding of Java 17+ fundamentals and frameworks such as Spring Boot - Strong knowledge of object-oriented programming paradigms, multithreading, messaging technologies, and computer networks - Experience with low-latency programming techniques and technologies such as Inter-Process Communication (IPC), memory-mapped files, and ring buffers - Experience with gRPC and Google Protocol Buffers - Experience working on distributed systems, including detailed knowledge of distributed-systems design patterns - Detailed knowledge of relational databases (e.g., PostgreSQL, CockroachDB) including resiliency, recoverability, scalability, and security - Experience with distributed messaging technologies such as Kafka - 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 practices - Experience with diagramming tools (PlantUML, Lucid, Draw.io, Visio) and technical writing; passion for technical innovation, staying current with emerging technologies, understanding the SDLC and agile methodologies, and demonstrated coaching/mentoring experience Preferred qualifications, capabilities, and skills - Hands-on experience with another statically compiled language such as Golang, Rust, or C++. - Experience with Apache Ignite, GridGain, Hazelcast, or Redis. - Experience with infrastructure as code software such as Terraform. - Awareness of key architectural patterns/approaches, algorithms, data structures, cryptography, security protocols (e.g., TLS and OAuth/OIDC), secure system design and Threat Modelling.