Lead Software Engineer - AI Operations
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
- 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