This is your chance to change the path of your career and guide multiple teams to success at one of the world's leading financial institutions. As a Manager of Software Engineering at JPMorgan Chase within the Consumer and Community Banking , you lead multiple teams and manage day-to-day implementation activities by identifying and escalating issues and ensuring your team’s work adheres to compliance standards, business requirements, and tactical best practices.
Job responsibilities
- Provides guidance to immediate team of software engineers on daily tasks and activities
- Sets the overall guidance and expectations for team output, practices, and collaboration
- Anticipates dependencies with other teams to deliver products and applications in line with business requirements
- Leads team adoption of enterprise-authorized AI-assisted engineering practices and SDLC/TLM automation to improve delivery speed, quality, and operational outcomes, while setting expectations for human validation, secure handling of inputs/outputs, and consistent use of reusable patterns across teams.
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation and support capacity unlock initiatives.
- Manages stakeholder relationships and the team’s work in accordance with compliance standards, service level agreements, and business requirements
- Creates a culture of diversity, opportunity, inclusion, and respect for the team members and prioritizes diverse representation Required qualifications, capabilities, and skills
- Formal training or certification on software engineering* concepts and 5+ years applied experience. In addition, demonstrated coaching and mentoring experience
- Proficiency developing backend services in Java with Spring Boot within microservices architectures.
- Ability to design and implement RESTful web services and APIs.
- Hands-on experience defining cloud infrastructure as code with Terraform and operating services AWS.
- Experience containerizing and orchestrating applications with Docker and Kubernetes.
- Practical experience with relational and NoSQL databases, including Postgres, Cassandra, MongoDB, and Redis.
- Experience building and maintaining event streaming solutions using Kafka or RabbitMQ.
- Well-versed in DevOps and SRE practices, including CI/CD with Jenkins and observability using Splunk and Grafana.
- Experience leading responsible adoption of enterprise-authorized AI-assisted development and delivery tools across engineering teams, including defining ways of working (review/validation expectations), measuring outcomes, and ensuring secure handling of data.
- Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, resiliency/security implications, and governance expectations; ability to coach engineers on compliant and effective usage.
Preferred qualifications, capabilities, and skills
- Cloud certification in AWS.
- Experience implementing observability and SRE practices using Splunk and Grafana.
- Experience with performance tuning, capacity planning, and reliability engineering for high-throughput services.
- Familiarity with secure coding practices and threat modeling