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Director of Software Engineering - Backend ( Java, AWS, AI)

Director of Software Engineering - Backend ( Java, AWS, AI)

JP Morgan Chase & Co.
Fresher
Early Applicant
  • Posted 2 hours ago
  • Be among the first 10 applicants

Job Description

If you are a software engineering leader ready to take the reins and drive impact, we've got an opportunity just for you.

As a Director of Software Engineeringat JPMorganChase within the Consumer & Community Banking , you lead a technical area and drive impact within teams, technologies, and projects across departments. Utilize your in-depth knowledge of software, applications, technical processes, and product management to drive multiple complex projects and initiatives, while serving as a primary decision maker for your teams and be a driver of innovation and solution delivery.

Job responsibilities

  • Single threaded owner for delivering end-to-end impactful technical solutions collaborating with the product, business partners and other Engineering teams.
  • Leads technology and process implementations to achieve functional technology objectives
  • Sets direction and governance for agentic AI-enabled engineering and SDLC/TLM automation within a technical area to drive measurable improvements in speed, quality, and operational outcomes (e.g., AI-orchestrated delivery workflows, release readiness controls, automated test modernization, and incident triage acceleration), while establishing guardrails for validation, security, resiliency, traceability, and reuse 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 at scale.
  • Makes decisions that influence teams resources, budget, tactical operations, and the execution and implementation of processes and procedures
  • Carries governance accountability for coding decisions, control obligations, and measures of success such as cost of ownership, maintainability, and portfolio operations
  • Delivers reusable technical solutions that can be leveraged across multiple businesses and domains
  • Influences peer leaders and senior stakeholders across the business, product, and technology teams
  • Champions the firm's culture of diversity, opportunity, inclusion, and respect
  • Champions every day innovation

Required qualifications, capabilities, and skills

  • Formal training or certification onsoftware engineering concepts and 10+ years applied experience. In addition, 5+ years of experience leading technologists to manage, anticipate and solve complex technical items within your domain of expertise

  • Leadership Experience in Financial domain with strong Engineering and Data expertise
  • Experience in championing AI led engineering and delivering significant productivity gains
  • Experience leading adoption of agentic AI-enabled engineering practices (using enterprise-authorized tools within the work environment) across teams, including defining operating expectations (human-in-the-loop validation, quality gates), measuring outcomes, and ensuring secure handling of sensitive inputs/outputs.
  • Strong understanding of responsible AI use and control expectations in engineering workflows, including data sensitivity, resiliency/security implications, and governance ability to influence leaders on safe scaling patterns and reuse.
  • Experience developing and leading cross-functional teams of technologists
  • Experience with hiring, developing, and recognizing talent
  • Practical cloud native experience
  • Expertise in Computer Science, Computer Engineering, Mathematics, or a related technical field
  • A continuous learner and demonstrate ability to adapt and lead a change.

Preferred qualifications, capabilities, and skills

  • Experience in Wealth Management Sub-Domain
  • Experience in working with Lead Management.
  • Experience working at Architecture and Design Level

Key Skills

SDLC TLM automation

AI-orchestrated delivery workflows

release readiness controls

cloud native experience

automation capabilities

automated test modernization

incident triage acceleration

responsible AI use and control

agentic AI-enabled engineering

Data expertise

Software Development Life Cycle toolchain

enterprise-authorized AI-assisted development

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