Manager of Software Engineering

JPMorgan Chase JPMorgan Chase · Banking · India · Consumer & Community Banking

Manager of Software Engineering at JPMorgan Chase within the Consumer & Community Banking Team, leading multiple teams and managing day-to-day implementation activities. The role involves guiding teams on daily tasks, setting output expectations, leading adoption of enterprise-authorized AI-assisted engineering practices and SDLC/TLM automation, and managing stakeholder relationships in accordance with compliance standards. Requires formal training/certification on Java and 5+ years of applied experience, with proficiency in Java, SQL, Spring boot, Micro services, AWS, and RDBMS. Experience leading responsible adoption of AI-assisted development tools and understanding of responsible AI use in engineering workflows are also required.

What you'd actually do

  1. Provides guidance to immediate team of software engineers on daily tasks and activities
  2. Sets the overall guidance and expectations for team output, practices, and collaboration
  3. 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.
  4. 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.
  5. Manages stakeholder relationships and the team’s work in accordance with compliance standards, service level agreements, and business requirements

Skills

Required

  • Java concepts and 5+ years applied experience
  • coaching and mentoring experience
  • delivering system design, application development, testing, and operational stability
  • Java
  • SQL
  • Spring boot
  • Micro services
  • AWS
  • RDBMS; Oracle or PostgresSQL
  • leading responsible adoption of enterprise-authorized AI-assisted development and delivery tools
  • defining ways of working (review/validation expectations)
  • measuring outcomes
  • ensuring secure handling of data
  • Understanding of responsible AI use in engineering workflows
  • data sensitivity considerations
  • resiliency/security implications
  • governance expectations
  • coach engineers on compliant and effective usage
  • automation and continuous delivery methods
  • AWS EC2
  • AWS Lambda
  • AWS KMS
  • AWS ECS
  • AWS EKS
  • AWS S3
  • EMR
  • Athena
  • SQS
  • EventBridge
  • PostgresSQL
  • Cloud Infrastructure Provisioning Tools like Terraform & Cloud Formation
  • agile methodologies
  • CI/CD
  • Application Resiliency
  • Security
  • software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)

Nice to have

  • Experience working at code level
  • Practical cloud native experience
  • In-depth knowledge of the financial services industry and their IT system

What the JD emphasized

  • enterprise-authorized AI-assisted engineering practices
  • responsible AI use in engineering workflows
  • leading responsible adoption of enterprise-authorized AI-assisted development and delivery tools