Lead Software Engineer - Full Stack

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 - Full Stack at JPMorgan Chase within the Enterprise Technology - Network 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.

This role is hands-on and suited for seasoned full stack engineers who can own end-to-end delivery-from system design through implementation, deployment on Kubernetes, and production operations (monitoring, troubleshooting, and performance tuning).

Job responsibilities



* Executes creative software solutions, design, development, and technical troubleshooting with the ability to think beyond routine or conventional approaches to build solutions or break down technical problems


* Owns end-to-end full stack delivery across; Frontend (React/TypeScript), Backend (Python services), Data/Workflow Services (Apache Airflow - DAG design) and Database (CockroachDB - data modeling)


* Designs and delivers scalable, highly available services and user experiences for large-scale applications; drives architecture decisions that improve throughput, latency, reliability, and operability


* Builds and maintains cloud-native deployments on Kubernetes, including configuration, scaling strategies, and operational readiness (health checks, rollouts, rollback strategies, capacity considerations)


* Drives monitoring, observability, and performance tuning across the stack using tools such as Splunk and Grafana (and related logging/metrics/tracing patterns); leads root-cause analysis and remediation


* 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 informa...