SR Director of Software Engineering – Trust and Safety Engineering

SR Director of Software Engineering – Trust and Safety Engineering

Tampa, FL, United States and 2 more

• Job Identification
• Job Category Software Engineering
• Business Unit Commercial & Investment Bank
• Posting Date 06/30/2026, 04:28 PM
• Locations 10410 Highland Manor Dr, Tampa, FL, 33610, US
• Job Schedule Full time

Your opportunity to make a real impact and shape the future of financial services is waiting for you. Let’s push the boundaries of what's possible together.

As a Senior Director of Software Engineering at JPMorgan

Chase within the Commercial and Investment Bank Payments Technology Fraud Engineering team, you lead multiple technical areas, manage the activities of multiple departments, and collaborate across technical domains. Your expertise is applied cross-functionally to drive the adoption and implementation of technical methods within various teams and aid the firm in remaining at the forefront of industry trends, best practices, and technological advances.

In this role, you will play a critical part in advancing fraud investigation capabilities and safeguarding payments processing across the organization.

Job responsibilities

• Lead multiple technology and process implementations across departments to achieve firmwide technology objectives
• Directly manage multiple areas with strategic transactional focus
• Provide leadership and high-level direction to teams while frequently overseeing employee populations across multiple platforms, divisions, and lines of business
• Act as the primary interface with senior leaders, stakeholders, and executives, driving consensus across competing objectives
• Manage multiple stakeholders, complex projects, and large cross-product collaborations
• Sets and scales multi-department strategy for agentic AI-enabled engineering and SDLC/TLM automation (using enterprise-authorized tools within the work environment) to drive firmwide objectives (speed, scalability, reliability, and cost-to-serve), including portfolio-level standards for AI-orchestrated delivery workflows, release governance, automated test modernization, resilience engineering, and incident response acceleration; establishes guardrails for validation, security, resiliency, traceability, and reuse.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to drive cross-domain reuse and measurable capacity unlock outcomes across departments.
• Drive the development and delivery of high throughput, low latency production systems for fraud prevention
• Oversee cross-functional engineering teams, including application, data, and SRE disciplines
• Guide the adoption of Dev Ops practices, CI/CD, and infrastructure as code across teams
• Ensure operational stability, observability, and reliability of distributed, cloud-native architectures

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 10+ years applied experience, including 5+ years leading technologists to manage, anticipate, and solve complex technical items within your domain of expertise
• Strong background in Java-based backend systems (e.g., Spring Boot, microservices)
• Experience developing or leading large or cross-functional teams of technologists (application, data, SRE)
• Deep understanding of distributed systems design and cloud-native architectures
• Experience with cloud platforms (e.g., AWS, GCP, or Azure)
• Proven track record delivering high throughput/low latency production systems
• Strong experience with Dev Ops practices, CI/CD, and infrastructure as code
• Familiarity with observability tools (monitoring, logging, tracing)
• Demonstrated prior experience influencing across highly matrixed, complex organizations and delivering value at scale
• Experience leading multi-organization adoption of agentic AI-enabled engineering operating models (using enterprise-authorized tools within the work environment), including defining governance (human-in-the-loop decisioning, quality gates), measurement frameworks, and secure handling of sensitive inputs/outputs across teams.
• Deep understanding of…