The Senior Manager of Software Engineering will mentor technical teams, oversee software engineering projects, manage resources, and influence budget decisions. Responsibilities include ensuring collaboration, mitigating issues, coaching engineers, and enhancing operational efficiency. The role focuses on advancing financial technology with AI and ML capabilities.
Job Description
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 Consumer and community banking- Data technology, you serve in a leadership role by providing technical coaching and advisory for multiple technical teams, as well as anticipate the needs and potential dependencies of other functions within the firm. As an expert in your field, your insights influence budget and technical considerations to advance operational efficiencies and functionalities.
Job responsibilities
- Provide overall direction, oversight, and coaching for a team of entry-level to mid-level software engineers that work on basic to moderately complex tasks
- Be accountable for decisions that influence teams' resources, budget, tactical operations, and the execution and implementation of processes and procedures
- Ensures successful collaboration across teams and stakeholders
- Identifies and mitigates issues to execute a book of work while escalating issues as necessary
- Provides input to leadership regarding budget, approach, and technical considerations to improve operational efficiencies and functionality for the team
- Creates a culture of diversity, equity, inclusion, and respect for team members and prioritizes diverse representation
- Enable the Gen AI platform and implement the Gen AI Use cases ,LLM fine tuning and multi agent orchestration
- Manage an AIML Engineering scrum team which includes ML engineers, Senior ML engineers and lead ML engineer.
Required Qualifications, Capabilities, and Skills
- Formal training or certification on software engineering concepts and 5+ years of applied experience
- Extensive practical experience with Python and AWS cloud services, including EKS, EMR, ECS, and DynamoDB.
- Experience in DataBricks ML lifecycle development.
- Advanced knowledge in software engineering, AI/ML, machine learning operations (MLOps), and data governance.
- Demonstrated prior experience in leading complex projects, including system design, testing, and ensuring operational stability.
- Expertise in computer science, computer engineering, mathematics, or a related technical field.
- Understanding of large language model (LLM) approaches, such as Retrieval-Augmented Generation (RAG)
Preferred qualifications, capabilities, and skills
- Real-time model serving experience with Seldon, Ray, or AWS SM
- Experience in agent-based model
Top Skills
AWS
Databricks
DynamoDB
Ecs
Eks
Emr
Mlops
Ray
Seldon
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