As a Manager of Software Engineering at JPMorgan Chase within the Consumer and Community Banking , youlead multiple teams and manage day-to-day implementation activities by identifying and escalating issues and ensuring your team9s 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 team9s 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