JPMorgan Chase & Co.

Senior Manager of Software Engineering

JPMorgan Chase & Co. · Hyderabad, Telangana, India

Financial Services · 10,001+ employees

3 h ago Closes in 6d
Senior (5-10 yrs) Full-time India
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About the role

The Senior Manager will provide technical direction and coaching to software engineering teams while managing resources, budgets, and operational processes. They are responsible for scaling AI-assisted engineering practices and ensuring the delivery of high-quality, secure, and resilient software solutions.

What they look for

Software Engineering Team Leadership Technical Coaching AI-assisted Development SDLC Site Reliability Engineering Cloud Native Budget Management Stakeholder Management Operational Efficiency Mentoring Process Improvement Security Resiliency Automation

Requirements

Candidates must have at least 5 years of applied software engineering experience and a proven track record of leading technical teams. Proficiency in SDLC toolchains, cloud-native environments, and the ability to drive strategic initiatives through effective stakeholder collaboration are required.

Full 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 Infrastructure Platforms team, 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
  • Accountable for decisions that influence teams’ resources, budget, tactical operations, and the execution and implementation of processes and procedures
  • Sets and scales operating practices for enterprise-authorized AI-assisted engineering and SDLC/TLM automation across multiple teams to improve delivery speed, quality, and operational outcomes; establishes measurable expectations (e.g., throughput, defect reduction, reliability) and ensures consistent validation, security, resiliency, and reuse of proven patterns.
  • Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to drive efficiency and support capacity unlock initiatives across teams, prioritizing reuse of existing firm technology assets.
  • Ensures successful collaboration across teams and stakeholders
  • Identifies and mitigates issues to execute a book of work while escalating issues as necessary
  • Supports the adoption of site reliability engineering best practices within your team
  • Provides input to leadership regarding budget, approach, and technical considerations to improve operational efficiencies and functionality for the team

Required qualifications, capabilities, and skills

  • Formal training or certification on software engineering concepts and 5+ years applied experience .
  • Experience leading teams of technologists
  • Ability to guide and coach teams on approach to achieve goals aligned against a set of strategic initiatives
  • Ability to contribute to large and collaborative teams by presenting information in a logical and timely manner with compelling language and limited supervision
  • Ability to proactively recognize road blocks and demonstrates interest in learning technology that facilitates innovation
  • Ability to identify new technologies and relevant solutions to ensure design constraints are met by the software team
  • Experience leading multi-team adoption of enterprise-authorized AI-assisted development and delivery tools, including defining governance/ways of working (human-in-the-loop validation, quality gates), measuring outcomes, and ensuring secure handling of sensitive inputs/outputs.
  • Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, resiliency/security implications, and control expectations; ability to coach managers/leads and influence leaders on safe scaling patterns.
  • Experience with hiring, developing, and recognizing talent
  • In-depth knowledge of the services industry and their IT systems
  • Practical cloud native experience

Preferred qualifications, capabilities, and skills

  • Experience working at code level
  • Ability to initiate and implement ideas to solve business problems
  • Passion for learning new technologies and driving innovative solutions.