Senior Manager of Software Engineering - Machine Learning & Cloud

When you mentor and advise multiple technical teams and move financial technologies forward, it’s a big challenge with big impact. You were made for this.

As a Senior Manager of Software Engineering at JPMorgan Chase within the Corporate Technology- Consumer & Community Bank Risk group, 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 and lead, 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

• Executes standard software solutions, design, development, and technical troubleshooting

• Provides Technical Leadership, guidance and direction to other team members

• Writes secure and high-quality code using Python or Java programming languages

• Manage a team of 10 people and provide guidance to emerging talents

• Establish standards, guidance and best practices for the technical aspects in the team

• Applies knowledge of tools within the Software Development Life Cycle toolchain to improve the value realized by automation

• Applying technical troubleshooting skills to analyze and resolve technical issues

• Leverages Cloud services to build ML pipeline to implement, deploy and productionize ML Models

• Works with Business stakeholders and Product Owners to understand requirements.

• Handle MLOps tasks and any associated infrastructure or production changes in coordination with SRE.

Required qualifications, capabilities, and skills:

• Formal training or certification on software engineering concepts and 5+ years applied experience. In addition, 2 + years of experience leading technologists to manage and solve complex technical items within your domain of expertise

• Hands-on experience in software engineering, system design, and application development.

• Hands-on practical experience in system design, application development, testing, and operational stability.

• Demonstrates a proactive attitude and eagerness to learn emerging technologies, including AI and ML.

• Experience in technologies such as pyspark, Kafka, Terraform, Kubernetes.

• Experience with AWS services, including but not limited to ECS, EMR, Lambda, EC2 and SageMaker

• Experience in programming languages such as Python or Java.

• Understanding of and ability to learn the basic architecture of Cloud services and usage.

• Experience working with databases such as Oracle or Cassandra.

• Exposure to Agile and scrum methodologies.

• Familiarity with CI/CD, Application Resiliency, and Security.

Preferred qualifications, capabilities, and skills

• Background with Machine Learning Frameworks and MLOps.

• Python Machine Learning library and ecosystem experience (Pandas and Numpy etc.)

• Experience or knowledge in Databricks.