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 Engineering at JPMorganChase within 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
- Leads technology and process implementations to achieve functional technology objectives
- 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
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.
- Own end-to-end delivery of large-scale credit card platform initiatives, managing scope, risk, and dependencies across multiple workstreams
- Provide architectural direction for platform engineering, designing highly available, fault-tolerant systems capable of processing transactions at scale with minimal latency
- Champion the adoption of AI-driven development practices, including AI-assisted code generation, automated testing, and predictive defect analysis
- Partner with risk, compliance, and information security teams to embed controls into the software development lifecycle
- Evaluate and integrate Huge data processing, data streaming, real-time analytics, and event-sourcing patterns to enable new payments products and features
Collaborate with enterprise architecture and platform engineering teams to ensure alignment with technology standards and cloud strategy
Required qualifications, capabilities, and skills
- Formal training or certification on software 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
- Proven experience architecting and delivering large-scale, high-availability distributed systems processing high-volume, low-latency workloads
- Hands-on expertise with modern enterprise technology stacks, including Java/Kotlin, reactive and asynchronous frameworks, event-promoten architectures, containerized environments, and infrastructure-as-code tools
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.
- Ability to promote complex, multi-workstream delivery programs from technical strategy through production release
- Experience embedding security, compliance, and regulatory controls into engineering workflows and CI/CD pipelines
- Experience in the banking or financial services domain, with Digital Wallet or payments industry experience
- Extensive experience with AWS services, including architecture, deployment, and optimization of cloud-based solutions.
Preferred qualifications, capabilities, and skills
- Proficiency with architectural modeling languages such as UML or the C4 model, and familiarity with enterprise architecture frameworks
- Hands-on experience with event-driven architecture patterns, including technologies such as Kafka, event sourcing, and CQRS
- Exposure to AI/ML tooling, large language model integration, or AI-assisted software development practices
- Demonstrated expertise in building 0-to-1 applications, taking products from concept to launch.
- Skilled in processing and managing large volumes of data for settlement and reconciliation workflows, ensuring accuracy and efficiency.
