Senior Lead Software Engineer - AI, Cloud & Security

JPMorganChase

Jersey City (NJ)

On-site

USD 140,000 - 210,000

Full time

14 days+

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Job summary

JPMorgan Chase in Jersey City seeks a Senior Lead Software Engineer to guide design and delivery of secure, scalable technology products within the Consumer and Community Banking technology team. You will drive architecture decisions, mentor engineers, and implement AI-assisted development practices to improve quality and speed.

The role requires deep Java expertise, strong SDLC knowledge, and experience with cloud, containers, and CI/CD.

Qualifications

Formal training or certification in software engineering concepts and 5+ years applied experience.
Hands-on experience delivering system design, application development, testing, and operational stability.
Advanced proficiency in Java.
Proficiency in automation and continuous delivery methods.
Expertise in all aspects of the Software Development Life Cycle.
Advanced understanding of agile methodologies such as CI/CD, application resiliency, and security.
Proficiency in technologies such as cloud, AI/ML, mobile, etc.
Experience leading the use of approved AI-assisted software development tools and validating AI outputs for correctness, performance, and security.
Strong understanding of responsible AI use in engineering workflows, including data sensitivity and secure handling of inputs/outputs.
Experience designing, deploying, and managing containerized applications using Kubernetes.
In-depth knowledge of the financial services industry and its IT systems.

Responsibilities

Provide technical guidance and direction to business, technical teams, contractors, and vendors.
Develop secure, high-quality production code; review and debug code written by others.
Drive decisions that influence product design, application functionality, and technical operations and processes.
Serve as a function-wide subject-matter expert in one or more focus areas.
Lead adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes, establishing consistent validation standards.
Apply knowledge of the Software Development Life Cycle toolchain, including AI-assisted development and automation, to increase automation value.
Advocate firm-wide framework, tool, and practice usage within the engineering community.
Influence peers and project decision-makers to consider leading-edge technologies.
Contribute to a culture of diversity, opportunity, inclusion, and respect.