Lead Software Engineer - Proxy​/SSE Network Security

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As a Lead Software Engineer at JPMorgan

Chase within the Corporate Sector – Enterprise Technology, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives.

• Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
• Develops secure high-quality production code, and reviews and debugs code written by others
• Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
• 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.
• Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
• Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
• Own the US perimeter, proxy, and SSE engineering roadmap and execution, including intake, prioritization, dependency management, delivery governance, and stakeholder alignment across cybersecurity, network services, operations, and application and platform teams.
• Define and operationalize standards, reference architectures, and reusable engineering patterns for perimeter and egress controls, including forward proxy and secure web gateway patterns, access brokering and identity-aware access concepts where applicable, enterprise egress enforcement, segmentation and policy patterns, and design considerations such as TLS inspection and traffic steering, expressed at a pattern and control-integration level.
• Provide engineering leadership across edge and connectivity adjacencies that materially impact perimeter posture and service delivery, including Cisco and Arista edge environments, colocation and interconnect ecosystems (including Equinix Fabric), and cloud adjacency patterns including AWS Direct Connect and AWS Private Link, with awareness of multi-cloud interconnect considerations.
• Establish and run governance mechanisms that accelerate remediation while preserving strong controls, including backlog governance, exception handling, risk acceptance and closure workflows, traceability and auditability requirements, and reporting that ties delivery milestones to risk reduction and resilience outcomes.
• Drive operational excellence at scale for perimeter, proxy, and SSE services in the US, including incident, change, and problem management rigor, observability and resiliency validation practices, automation to improve repeatability and evidence quality, reduction of client and partner impact, and execution of Technology Lifecycle Management (TLM) and modernization outcomes tied to stability and risk reduction.

• 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
• Advanced in one or more programming language(s)
• Demonstrated experience leading effective use of approved AI‑assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
• Demonstrated experience delivering regional execution ownership in the US (or North America) for infrastructure and/or security platforms, including prioritization, cross‑team coordination, and sustained accountability for operational and delivery outcomes.
• Experience supervising engineers and delivering cross‑team remediation,…