Join a team where your engineering expertise shapes the digital experiences of millions. At JPMorganChase, we invest in our engineers, champion innovation, and give you the tools, scale, and autonomy to build technology that truly matters.
As a Senior Lead Software Engineer at JPMorganChase within the Consumer & Community Banking Digital Technology team, you will serve as a subject matter expert and technical leader, driving the design and delivery of secure, scalable, AI-enabled products that define next-generation customer experiences. You will work at the intersection of engineering excellence and responsible AI adoption, influencing how teams build, validate, and scale intelligent solutions across the organization. Your work will directly impact how millions of customers interact with our digital platforms every day.
Job responsibilities
- Architect and govern agentic AI-enabled engineering workflows using enterprise-authorized tools to improve delivery speed, code quality, and operational outcomes at scale, including AI-driven pull request review assistance, test generation and maintenance, release readiness checks, and incident triage and root-cause acceleration
- Define guardrails for validation, security, resiliency, and reuse of AI-assisted engineering practices across teams, establishing consistent standards for human-in-the-loop oversight, auditability, and secure handling of sensitive data
- Design and build complex, scalable coding frameworks using appropriate software design patterns that are leveraged across teams and functions
- Develop secure, high-quality production code and conduct rigorous code reviews and debugging across the engineering organization
- Help define enterprise-scale, target-state AI-enabled architecture for solutions within the Consumer & Community Banking division to deliver best-in-class and next-generation customer experiences
- Collaborate with product and engineering leaders to define roadmaps and solution architectures aligned to target-state goals
- Apply 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 at scale
- Advise cross-functional teams on technological matters within your domain of expertise, serving as the go-to subject matter expert for AI-enabled engineering practices
- Drive team adoption of enterprise-authorized AI-assisted engineering practices, including AI-assisted code review and refactoring, test strategy acceleration, and incident and root-cause analysis support
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Hands-on practical experience delivering system design, application development, testing, and operational stability
- Expert proficiency in one or more programming languages
- Demonstrated experience designing and leading adoption of agentic AI-enabled development practices using enterprise-authorized tools, including setting standards for human-in-the-loop validation, auditability and traceability of changes, and secure handling of sensitive data
- Strong understanding of responsible AI use and control expectations in engineering workflows, including security and resiliency implications, data sensitivity, and risk-based governance
- Ability to influence senior technical leaders on safe scaling patterns and reuse of AI-enabled engineering practices
- Experience applying expertise and emerging methods to determine solutions for complex technology problems across one or more technical disciplines
- Practical cloud-native experience
- Understanding of the business context and how technology decisions drive customer and organizational outcomes
Preferred qualifications, capabilities, and skills
- Degree in Computer Science, Computer Engineering, Mathematics, or a related technical field
- Advanced knowledge of software architecture, applications, and technical processes with considerable depth in one or more disciplines such as cloud, artificial intelligence, machine learning, or mobile
- Experience working within large-scale, highly regulated enterprise environments with complex cross-functional stakeholder landscapes
- Familiarity with modern DevSecOps practices and toolchains that support continuous delivery and operational resilience
- Experience mentoring or coaching engineers and contributing to the technical growth of a team