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 JPMorgan Chase within the Consumer & Community Banking, 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.

You’ll harness semantic domain models and attribute‑based access control to power dynamic, self‑service journeys across a wide spectrum of platforms and services—so the right capabilities, data, and controls surface at the right moment, automatically, delighting customers and accelerating delivery.

Job responsibilities

• Provide overall direction, oversight, and coaching for a team of entry-level to mid-level software engineers, including hands-on guidance in Java development and best practices for building robust, scalable applications.
• Lead the design, development, and deployment of cloud-native, heavily distributed systems and solutions on AWS, ensuring high availability, scalability, and resilience.
• Be accountable for decisions that influence teams’ resources, budget, tactical operations, and the execution and implementation of processes and procedures, with a focus on optimizing cloud infrastructure and distributed architectures.
• Ensure successful collaboration across teams and stakeholders, fostering alignment on technical design, cloud adoption, and distributed system integration.
• Provide input to leadership regarding budget, approach, and technical considerations to improve operational efficiencies and functionality for the team, including cloud cost optimization and architectural trade-offs.
• Guide and coach teams on approach to achieve goals aligned against a set of strategic initiatives, including adoption of cloud-native patterns and DevOps practices.
• Drive the strategy and delivery of self-service platforms and capabilities at scale (e.g., developer portals, automated environment provisioning, and pave-the-path guardrails) to improve engineering productivity and reduce lead time to value.
• Define, implement, and govern enterprise-grade authorization models using RBAC and ABAC in partnership with Cyber and IAM, enforcing least privilege and policy consistency across platforms and services.
• Establish and evolve semantic domain models and corresponding data architectures; apply graph database patterns where appropriate to enable relationship-centric capabilities and discovery.
• Architect self-service journeys powered by semantic models and ABAC—dynamically routing, assembling, and authorizing capabilities across diverse services and channels to reduce friction and speed time to value.
• Apply orchestration and choreography patterns that leverage semantic context and attributes; design for observability, idempotency, compensation, and graceful degradation to ensure resilient, high trust experiences end to end, with a strong emphasis on distributed system reliability and cloud-native monitoring.

Required qualifications, capabilities, and skills

• 10+ years of experience leading technologists to manage and solve complex technical items within your domain of expertise, including hands-on Java development and distributed system design.

• Deep expertise in Java, including modern frameworks (Spring Boot, etc.), concurrency, and performance tuning for large-scale, cloud-native applications.

• Proven experience architecting, building, and operating distributed systems on AWS, leveraging services such as ECS/EKS, Lambda, S3, DynamoDB, and API Gateway.

• Experience leading teams of technologists, guiding them through technical challenges in cloud-native and distributed environments.

• Experience with hiring, developing, and recognizing talent, with a focus on fostering technical excellence and innovation.

• In-depth knowledge of the services industry and their IT systems, with practical experience in cloud migration and modernization.

• Proven experience building and operating self-service systems at large scale (e.g., automated provisioning, golden paths, developer enablement).

• Deep experience implementing and governing RBAC/ABAC authorization models at enterprise scale, including role engineering, attribute policy design, and entitlement management.

• Extensive experience with semantic modeling and translating those models into operational data stores; hands-on experience with graph-oriented data modeling and graph databases.

• Enterprise architecture experience with a strong engineering focus, specifically in platform and service delivery (roadmaps, modernization, migration patterns, and operationalization), including distributed system design and cloud-native architecture.

• Strong understanding of how semantic models and ABAC combine to enable dynamic self-service journeys across many services—including attribute sourcing, policy decisioning, and runtime enforcement integrated with APIs, gateways, and workflow engines.

Preferred qualifications, capabilities, and skills

• Hands-on experience working at code level, with deep proficiency in Java and distributed system development.
• Experience with graph databases and graph query languages (e.g., property graphs, Gremlin or similar).
• Experience defining platform product metrics and SLOs, and driving adoption of self-service capabilities across large engineering communities.
• Familiarity with policy-as-code approaches for authorization and platform guardrails, and with distributed tracing and event correlation across microservices.
• Hands-on experience using AI coding assistants (e.g., GitHub Copilot, Claude Code, or firm-approved equivalents) to accelerate secure, high-quality development, test automation, and code review within enterprise guardrails.
• Experience with cloud-native DevOps practices, including CI/CD pipelines, infrastructure as code (e.g., Terraform, CloudFormation), and automated testing in distributed environments.
• Strong knowledge of distributed system patterns (e.g., event-driven architecture, microservices, CQRS, saga orchestration) and cloud-native observability tools (e.g., AWS CloudWatch, OpenTelemetry).