JPMorgan Chase
Lead Software Engineer - Full Stack/AI Engineering Focus
545 Washington Blvd, Jersey City, NJ 07310
Full-time
First seen by offpeak October 21, 2026
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As a Lead Software Engineer at JPMorganChase within the Commercial & Investment Bank - Digital & Platform Services team, 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
- Design, develop, and deliver scalable, secure, and resilient full-stack solutions using Java/Spring Boot, React, and TypeScript, applying strong engineering judgment to meet functional and non-functional requirements while solving complex business and technical challenges.
- Own the end-to-end delivery lifecycle for strategic platform capabilities and application features, including requirements analysis, solution design, development, testing, deployment, production support, and continuous improvement.
- Lead the design and development of cloud-native, containerized microservices and platform services, emphasizing domain-driven design, API-first development, performance optimization, security, maintainability, and operational excellence.
- Drive technical architecture and design decisions across the technology stack, collaborating with product managers, architects, and engineering teams to ensure alignment with enterprise architecture standards and long-term technology strategies.
- Build and enhance high-performance backend services and APIs (REST/GraphQL), integrating with enterprise platforms, relational databases, search technologies, and distributed data systems.
- Develop modern operational and administrative user interfaces using React and TypeScript, delivering intuitive experiences that improve platform usability, productivity, and supportability.
- Design and implement event-driven and streaming architectures leveraging Kafka, including event modeling, schema governance, topic strategy, and resilient producer-consumer patterns to enable scalable and loosely coupled systems.
- Champion engineering excellence through code reviews, troubleshooting, refactoring, performance tuning, and mentoring, while raising quality standards across the team.
- Lead initiatives to improve application reliability, observability, and operational stability through automation, proactive monitoring, distributed tracing, incident management, root cause analysis, and continuous reduction of technical debt.
- Leverage enterprise-approved AI-assisted engineering tools and platforms to accelerate software delivery, improve developer productivity, automate repetitive tasks, and enhance code quality while adhering to established governance, security, and validation practices.
- Evaluate, design, and implement AI-powered and agentic solutions that optimize software development, operational workflows, system support, and engineering processes, ensuring measurable business and productivity outcomes.
- Formal training or certification on software engineering concepts and 5+ years applied experience
- 10+ years of hands-on software engineering experience building and supporting enterprise-scale applications.
- Strong expertise designing and developing backend services using Java, Spring Boot, distributed systems, and microservice architectures.
- 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
- Hands-on experience building and consuming APIs using REST and/or GraphQL.
- Strong experience with relational databases, SQL optimization, and data access patterns.
- Experience implementing event-driven and streaming architectures using Kafka or equivalent messaging platforms.
- Experience building modern frontend applications using React and TypeScript.
- Experience with observability and operational tooling such as Splunk, Grafana, Kibana, ELK, OpenTelemetry, Postman, or equivalent platforms.
- Proficiency with modern engineering tooling including Git, GitHub, Maven, Jenkins, SonarQube, IntelliJ IDEA, VS Code, Jira, and Confluence.
- Working knowledge of Python with experience using Python for automation, data processing, or AI-enabled solutions is highly desirable
- Experience designing and deploying AI agents and agentic workflows for software engineering, operations, or business process automation.
- Understanding of Model Context Protocol (MCP) and modern AI integration patterns.
- Knowledge of prompt engineering techniques, AI workflow design, and human-in-the-loop systems.
- Experience creating agentic automations that improve SDLC productivity, testing, code reviews, documentation generation, CI/CD operations, or incident management.
- Demonstrated ability to establish governance, validation, and quality controls for AI-generated code and solutions.
- Working knowledge of Elasticsearch/OpenSearch, including index design, query optimization, and operational management.