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 Kubernetes Product 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. With a growing industry focus around AI/ML, you will get to combineyour Kubernetes expertise with a solid understanding of machine learning and related frameworks. You will use your engineering skills and experience to deliver AI/ML based solutions which improve the operation of Kubernetes clusters and provide meaningful platform insight. 

Job responsibilities

 

Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems Develops secure high-quality production code, and reviews and debugs code written by others 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 Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies Adds to team culture of diversity, opportunity, inclusion, and respect Deliver AI/ML based solutions to improve Kubernetes platforms for JPMC Regularly provides technical guidance and direction to support the business and its technical teams

 

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 Advanced in one or more programming language(s) Proficiency in automation and continuous delivery methods Proficient in all aspects of the Software Development Life Cycle Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.) In-depth knowledge of the financial services industry and their IT systems Practical cloud native experience Experience applying data engineering and machine learning techniques Experience in Generative AI, LLMs and AI Agents  Preferred qualifications, capabilities, and skills   Experience working with modern private & public cloud infrastructure platforms - Kubernetes, AWS EKS Terraform, Ansible and other automation tools. Experience in multiple Cloud platforms like GCP GKE is a plus Knowledge of deep learning and ML Ops workflows Experience in Time Series analysis, including forecasting, anomaly detection, and trend analysis