Lead Software Engineer - Cloud DevOps & AI

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 JPMorganChase within the Consumer and Community Banking - Deposits 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.

Job responsibilities



* Design and implement CI/CD pipelines, infrastructure-as-code (IaC) frameworks, and container orchestration strategies leveraging tools such as Kubernetes, Docker, Terraform, and Spinnaker, while utilizing AI-driven automation to streamline deployment and management across cloud and on-premises environments.


* Lead the architecture, deployment, and management of cloud infrastructure in AWS, establishing and enforcing best practices for reliability, scalability, security, and cost optimization across all cloud environments.


* Drive the adoption of AI and machine learning capabilities within DevOps workflows, including intelligent monitoring, predictive analytics, and automated remediation, while evaluating and integrating AI-powered tools to continuously improve development velocity, system reliability, and operational efficiency.


* Lead the integration of intelligent agents for workflow automation, decision-making, and process optimization.


* Develop AI-powered observability solutions to monitor, analyze, and proactively manage application and infrastructure health, automating alerting, root cause analysis, and incident response using advanced ML techniques.


* Work closely with cross-functional teams including engineering, product, and operations to identify automation opportunities and deliver impactful solutions.


* Stay abreast of emerging AI/ML technologies, frameworks, and industry trends, driving continuous improvement by evaluating and implementing new tools, methodologies, and approaches.


* Provide hands-on technical guidance to a team of software and DevOps engineers, fostering a culture of innovation, accountability, and continuous learning.


* Conduct code reviews, architectural assessments, and design discussions to uphold engineering excellence.


* 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, in...