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 at JPMorgan Chase within the Corporate Technology, Identity & Access Management organization, 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
- Owns the architecture and multi-quarter technical roadmap for a multi-service observability platform running on Kubernetes, including the shared internal library contracts every service consumes and the versioning and migration strategy across consumers
- Designs the data layer end to end: schema and query design against distributed SQL and large-scale Oracle datasets, plus the migration tooling and rollback strategy that keeps changes safe in production
- Defines the observability model, owning how the platform emits and publishes metrics, logs, and traces, and setting the standard for what constitutes a meaningful signal versus noise
- Serves as the senior technical voice to leadership, control partners, and internal audit, translating platform evidence into decisions and control requirements into engineering work
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Hands-on practical experience delivering system design, application development, testing, and operational stability
- 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
- Proficient in all aspects of the Software Development Life Cycle
- Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
- In-depth knowledge of the financial services industry and their IT systems
- Practical cloud native experience
Preferred qualifications, capabilities, and skills
Hands-on depth with observability tooling at an advanced level: OpenTelemetry instrumentation, Prometheus-compatible metric backends, Splunk, and Grafana, including alert rule design, datasource configuration, and custom dashboarding beyond out-of-the-box panels.
Production experience with Kubernetes and Helm in a regulated enterprise environment, distributed SQL (CockroachDB or another Postgres-compatible distributed database), advanced SQL against large relational datasets, and schema migration tooling such as Liquibase.
Working knowledge of Identity and Access Management concepts including entitlements, certifications, provisioning and revocation, and SCIM, paired with experience building systems whose output is consumed by internal audit, regulators, or a formal control framework.