Lead Software Engineer - Python/ Java/ AWS

Overview In this role you will design, build, and operate critical tech solutions aligned with firm objectives. You contribute production code, raise engineering standards through mentorship, and drive reliability, security, and operational excellence across the software lifecycle. You will lead adoption of enterprise-authorized AI-assisted engineering practices to improve quality and delivery outcomes. You operate in a fast-paced, cross-functional environment within Asset & Wealth Management Technology, delivering scalable, secure software at scale. This is an opportunity to shape engineering practices and partner with vendors, startups, and internal teams to advance modern, resilient architectures. Compensation / Benefitsbase salaryincentive compensationcomprehensive health careretirement savings planbackup childcaretuition reimbursement ResponsibilitiesDesign, develop, and troubleshoot software with non-traditional approaches to solve complex problemsProduce secure, high-quality production code and review others' codePromote enterprise-authorized AI-assisted engineering practices to improve quality, speed, and operations with standardized validationLeverage SDLC tools and automation, including AI-assisted development, to maximize automation valueIdentify opportunities to automate recurring remediation and improve system stabilityLead evaluation sessions with external vendors and internal teams on architectural designs and applicabilityContribute to architecture decisions and technical documentation Key requirementsFormal training or certification in software engineering plus 5+ years of experienceStrong knowledge of microservices, REST APIs, event-driven design, and NoSQLExperience building cloud-native applications with AWS or comparable platformTrack record delivering at least two large, complex applications end-to-endKnowledge of CI/CD, DevOps toolchains, observability, and test-driven development in AgileProven experience leading use of approved AI-assisted development tools with validation for correctness, performance, and securityUnderstanding of responsible AI usage, data sensitivity, secure handling, resiliency, and security expectationsAdvanced understanding of application resiliency and securityStrong technical documentation skills (OpenAPI/Swagger)Familiarity with AI concepts and developer productivity tools (e.g., Microsoft Copilot)mentorshipleadershipcross-functional collaborationmicroservicesREST APIsevent-driven design