Lead Software Engineer-Full Stack/Multi-Cloud Security

Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we’re setting our businesses, clients, customers and employees up for success.

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.

As a Lead Software Engineer, Full Stack/Multi-Cloud Security at JPMorgan Chase within the Corporate Sector- Cloud Foundational 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. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.
 

Job responsibilities

•    Design and deliver multi-cloud security and continuous compliance solutions across Azure, AWS, and GCP.
•    Translate regulatory and policy requirements into technical controls, measurable KPIs/KRIs, and actionable engineering roadmaps.
•    Build control automation for preventive, detective, and corrective controls, including validation, evidence capture, exception handling, and remediation.
•    Implement audit-ready observability and traceability across services and delivery pipelines, including logs, metrics, lineage, and reporting.
•    Write high-quality, maintainable production code in Python or Go, and contribute to Java components where integration or platform requirements apply.
•    Engineer workflow orchestration for control execution, exception processing, and remediation across cloud and platform systems.
•    Build and optimize CI/CD pipelines using Jenkins, including DevSecOps quality and security gates.
•    Integrate enterprise systems and APIs including Jira, Confluence, Bitbucket, identity/authentication platforms, and cloud provider services.
•    Lead reliability and security engineering excellence: drive code/architecture reviews and standards; troubleshoot complex incidents with root-cause analysis; produce and maintain architecture documentation, ADRs, operational runbooks, control implementation standards; evaluate and integrate third-party tools; and lead responsible adoption of enterprise-approved AI-assisted engineering with robust validation for correctness, security, performance, resiliency, and data handling.
•    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

Required qualifications, capabilities, and skills  

•    Formal training or certification on software engineering concepts and 5+ years applied experience 
•    Proven experience across end-to-end backend delivery: system design, development, testing, deployment, and production operations.
•    Strong proficiency in Python or Go for building services and automation.
•    Hands-on CI/CD expertise using Jenkins in enterprise delivery environments.
•    Solid SDLC execution, including secure coding, test strategy, release governance, and operational support.
•    Cloud-native engineering experience on Azure, AWS, or GCP.
•    Experience implementing security, audit, and compliance controls in regulated environments.
•    Production experience with Kubernetes and workflow orchestration.
•    Ability to lead cross-functional delivery and mentor developers, with a strong focus on secure and resilient engineering practices.
•    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

Preferred qualifications, capabilities, and skills  

•    Experience delivering and operating security/compliance solutions  and familiarity with cloud-native security services (identity, key management, logging,               monitoring, policy enforcement) across Azure, AWS, and GCP.
•    Experience with policy-as-code and infrastructure-as-code (for example Terraform and cloud policy frameworks).
•    Experience building event-driven architectures and telemetry pipelines for control evidence and compliance reporting.
•    Experience integrating third-party security/compliance products into enterprise platforms.
•    Knowledge of financial-services regulatory and technology risk frameworks.
•    Experience applying AI-assisted tooling to security engineering and continuous compliance workflows.
•    Experience with API integration patterns and enterprise authentication/authorization mechanisms.