Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.

As a Senior Lead Software Engineer at JPMorgan Chase within the Corporate Sector in 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. In this role you will 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.

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

Develops secure and high-quality production code, and reviews and debugs code written by others. Automating the installation, upgrade, scaling, and management of a large and rapidly growing fleet of Kubernetes clusters. Develop custom platform control plane webhooks, CRDs and operators and more that provide a secure opinionated platform. Deliver AI/ML based solutions to improve Kubernetes platforms for JPMC. Automating Infrastructure-as-code, using Terraform, VRA, ansible and other infrastructure automation tools. Automating networking and O/S configuration from building images, configuring file system layouts, and automating BGP peering up through CRI, CNI & CSI configuration for Kubernetes clusters Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development. Drives decisions that influence the product design, application functionality, and technical operations and processes. Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors. Adds to the team culture of diversity, equity, inclusion, and respect.

 

Required qualifications, capabilities, and skills

Formal training or certification in Computer Science/ Software engineering and 5+ years of applied experience. Hands-on practical experience delivering system design, application development, testing, and operational stability. Proficiency in multiple modern programming languages, ideally including one of Go, Python, React, Java. Experience applying data engineering and machine learning techniques. Experience in Generative AI, LLMs and AI Agents  Experience in one or more major machine learning frameworks: Tensorflow, Pytorch, Scikit-Learn Experience working with modern private & public cloud infrastructure platforms - Kubernetes, AWS EKS Terraform, Ansible and other automation tools. Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages. Ability to tackle design and functionality problems independently with little to no oversight. Practical cloud native experience

Preferred qualifications, capabilities, and skills

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 Knowledge of industry-wide technology trends and best practices