We offer an opportunity to shape your career and embark on an exciting journey where you can push the boundaries of what’s possible.

As a Lead Software Engineer at JPMorgan Chase within the Commercial and Investment Banking – Applied AI/ML team, you are an integral member of an agile group dedicated to enhancing, building, and delivering trusted, market-leading technology products in a secure, stable, and scalable manner. As a core technical contributor, you will drive critical technology solutions across multiple technical domains and business functions, supporting the firm’s strategic objectives.

 Job Responsibilities

Design, develop, and troubleshoot software solutions for complex business challengesWrite secure, high-quality production code and review code from team membersIdentify and automate remediation of recurring issues to improve system stabilityLead architectural design sessions and provide technical guidance for on-premises and cloud systemsPromote adoption of new technologies through internal communities of practiceFoster a culture of diversity, equity, and respect within the teamDevelop and maintain applications using Python and AWSCreate and review architecture and design deliverables, ensuring best practices are followedIntegrate AI/ML solutions into domain-specific operations processing systemsLead code reviews, design discussions, and agile planning sessionsCollaborate with Site Reliability Engineering and monitoring teams to ensure system reliability and performance

Required Qualifications, Capabilities, and Skills

Formal training or certification on software engineering concepts and 5+ years applied experienceStrong experience building and running applications on AWS or other public cloud platformsAdvanced proficiency in Python programmingProven experience in system design, application development, testing, and maintaining operational stabilitySkilled in automation, continuous delivery, and the full Software Development Life CycleExperience with data processing pipelines and Directed Acyclic Graphs (DAGs) for machine learning or data workflowsDemonstrated expertise in cloud, artificial intelligence, and machine learning technologiesUnderstanding of IT systems in the financial services industryExperience with code reviews and agile methodologiesAbility to communicate technical concepts clearly to both technical and non-technical stakeholdersCommitment to continuous learning and creative problem-solving

Preferred Qualifications, Capabilities, and Skills

Experience with Cloud services, Infrastructure as Code (e.g., Terraform), and containerized application developmentFamiliarity with data storage systems such as Postgres and OpenSearch, and AWS services including S3, SageMaker, and BedrockPractical experience with Kubernetes, EKS, Docker, Kafka, MLOps, Large Language Model Operations (LLMOps), and event-driven systemsKnowledge of security best practices in cloud and application developmentExperience integrating AI/ML models into production environmentsAbility to mentor and guide junior engineersParticipation in technology events or software engineering communities