JPMorganChase
Senior Lead Software Engineer - Java/Python Full stack, Infrastructure
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Leads the design, development, and delivery of secure, scalable full-stack infrastructure solutions. Influences architecture, modernization, cloud adoption, automation, CI/CD, testing, and engineering standards. Provides technical leadership, code review, mentoring, and stakeholder coordination across Product, Architecture, Operations, SRE, vendors, and business teams. Drives responsible adoption of AI-assisted engineering tools while ensuring secure coding, validation, resiliency, and operational stability.
Join a team where your skills drive innovation and shape technology solutions. Experience growth and make a meaningful impact in a collaborative environment.
As a Senior Lead Software Engineer at JPMorgan Chase within the Infrastructure Platforms team, you will play a pivotal role in enhancing, building, and delivering trusted technology products in a secure, stable, and scalable way. You will influence architecture and design decisions, lead modernization initiatives, and enable high-quality delivery through your expertise. You will apply deep technical knowledge and problem-solving skills to address diverse challenges across various business functions, supporting the firm’s objectives.
Job responsibilities
- Design, develop, and deliver secure, scalable, and resilient full-stack solutions (UI, APIs, backend services, integrations, and database components).
- Lead requirements clarification, solution design, and delivery readiness by partnering with product leads, architects, stakeholders, and engineering teams.
- Drive technical decisions that influence product design, application functionality, architecture, and operational processes.
- Develop secure, high-quality production code; review and debug code written by others; establish engineering standards, reusable patterns, and best practices.
- Lead modernization and engineering excellence initiatives, including architecture reviews, cloud adoption, automation, reusable components, platform standards, and continuous improvement.
- Provide technical leadership, domain knowledge, guidance, coaching, and mentorship to engineers, technical leads, contractors, and vendors.
- 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 with Product, Architecture, Operations, SRE, and business stakeholders to ensure successful delivery, operational stability, and achievement of business objectives.
Required qualifications, capabilities and skills
- Formal training or certification on software engineering concepts and 12+ years applied experience.
- Hands-on experience delivering system design, application development, testing, operational stability, and architecture-led engineering solutions within large-scale enterprise environments.
- Advanced proficiency in one or more modern programming languages, with extensive experience developing, debugging, reviewing, and maintaining high-quality code.
- Strong full-stack SDLC experience across Java, Spring Boot, Python, React/Angular, including microservices, distributed systems, API design, and scalable application architectures.
- Practical experience with database technologies (Oracle, SQL Server, or similar), reporting/visualization tools, and enterprise integration patterns.
- Proven experience driving engineering excellence through automation, CI/CD, testing strategies, DevOps practices, and delivery optimization.
- Strong understanding of agile methodologies, application resiliency, secure engineering practices, and management of complex stakeholder, technology, and delivery dependencies.
- 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
- Proven ability to provide technical leadership, stakeholder management, mentoring, and guidance to engineers, technical leads, contractors, and vendors.
Preferred qualifications, capabilities and skills
- Familiarity with modern front-end technologies.
- Exposure to cloud technologies.
- Experience working in a product/platform environment.
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