Lead and mentor multiple engineering teams to design, build, and deploy scalable enterprise applications. Drive technical strategy, architecture, AI-assisted development adoption, SDLC automation, and cross-team collaboration while advising on budget, processes, and operational improvements.
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 JPMorganChase within the Home Lending, 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
As a Senior Manager of Software Engineering at JPMorganChase within the Home Lending, 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
- Lead the design and implementation of solutions to meet business requirements, ensuring high performance, scalability, and adherence to best practices.
- Provide technical guidance and mentorship to the development team, overseeing the development and deployment of applications.
- Conduct code reviews to ensure compliance with coding standards and guidelines and troubleshoot and resolve issues related to applications and integrations.
- Stay updated with the latest technologies and industry trends, contributing to the continuous improvement of development processes and methodologies. Be curious about modern technologies and comfortable with change and ambiguity.
- Ensure successful collaboration across teams and stakeholders and be accountable for decisions that influence teams’ resources, budget, tactical operations, and the execution and implementation of processes and procedures.
- Provide input to leadership regarding budget, approach, and technical considerations to improve operational efficiencies and functionality for the team.
- Accountable for decisions that influence teams’ resources, budget, tactical operations, and the execution and implementation of processes and procedures
- Lead and mentor a team of software engineers in the design, development, and deployment of scalable enterprise applications using Java, Spring Boot, and Python.
- 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.
Required qualifications, capabilities, and skills
- A Formal training or certification on software engineering concepts and 5+ years applied experience . In addition, 2 + years of experience leading technologists to manage and solve complex technical items within your domain of expertise
- Experience leading teams of technologists
- Extensive experience 10+ Years of experience in software engineering and architecture, with a focus on Java and AWS technologies
- Ability to guide and coach teams on approach to achieve goals aligned against a set of strategic initiatives
- 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
Preferred qualifications, capabilities, and skills
- Experience working at code level.
- A keen interest in staying ahead of modern development trends and experimenting with emerging technologies such as AI and Machine Learning.
- Ability to tackle design and functionality problems independently with little to no oversight
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