About The Role

As a Lead Software Engineer at JPMorgan Chase within the Consumer and Community Banking , 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

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 .

Preferred qualifications, capabilities, and skills

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.