SR Director of Software Engineering – Trust and Safety Engineering

J.P. Morgan’s Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world. 

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 JPMorganChase 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 DevOps 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 DevOps 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 responsible AI risk, controls, and resiliency/security expectations at scale, with demonstrated ability to advise senior leaders on safe adoption, portfolio governance, and reuse-first strategies.

Preferred qualifications, capabilities, and skills

• Experience designing and operating event-driven architectures (Kafka, Pulsar, etc.)
• Strong background in data engineering (ETL/ELT pipelines, streaming data, data lakes/warehouses)
• Experience implementing SRE principles (SLOs, error budgets, reliability engineering)
• Expertise in containerization and orchestration (Docker, Kubernetes)
• Experience with API design and management (gRPC, REST, GraphQL, API gateways)
• Familiarity with security and compliance in regulated environments (e.g., financial services)
• Strong experience with performance tuning and scalability optimization