As a Lead Software Engineer at JPMorgan Chase within the Consumer and Community Banking , youare 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 firm27s business objectives.

Job responsibilities

• Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
• Develops secure and high-quality production code, and reviews and debugs code written by others
• 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.
• Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
• Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Proficiency developing backend services in Java with Spring Boot within microservices architectures.
• Ability to design and implement RESTful web services and APIs.
• Hands-on experience defining cloud infrastructure as code with Terraform and operating services on  AWS.
• Experience containerizing and orchestrating applications with Docker and Kubernetes.
• Practical experience with relational and NoSQL databases, including Postgres, Cassandra, MongoDB, and Redis.
• Experience building and maintaining event streaming solutions using Kafka or RabbitMQ.

• Well-versed in DevOps and SRE practices, including CI/CD with Jenkins and observability using Splunk and Grafana.

   

• Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, testing, troubleshooting, or documentation) with demonstrated ability to critically evaluate and validate AI-generated outputs.

• Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations.

• Cloud certification in  AWS.
• Experience implementing observability and SRE practices using Splunk and Grafana.
• Experience with performance tuning, capacity planning, and reliability engineering for high-throughput services.
• Familiarity with secure coding practices and threat modeling.