Lead Software Engineer- Python / Quant Developer / Quant Research

Overview As a Lead Software Engineer in Python for Quant development, you will join the Asset and Wealth Management Technology team to build and scale a market-leading Quant Research Platform. You work closely with Quant Research to model development, validation workflows, and reusable Python libraries that standardize research-to-production patterns. You will apply your software lifecycle expertise across the stack to deliver secure, high-quality production code and drive responsible AI practices. This role offers the chance to shape a cross-functional platform at scale within a leading financial institution. Compensation / Benefitscompetitive total rewardsbase salary commensurate with role and locationbonus-based pay and/or discretionary incentive compensationcomprehensive health care coverageretirement savings plantuition reimbursement and mental health support ResponsibilitiesDesign, develop, and troubleshoot software solutions with non-routine, innovative approachesWrite secure, production-grade code and review others' codePromote enterprise AI-assisted engineering practices to improve quality, speed, and reliabilityLeverage the SDLC toolchain and AI-assisted development and automation to enhance valueIdentify opportunities to automate recurring issues to improve stabilityLead evaluation sessions with external vendors, startups, and internal teams on architectures and applicability Key requirementsFormal training or certification in software engineering and 5+ years of applicable experienceHands-on experience delivering system design, application development, testing, and operational stabilityStrong Python proficiencyExperience in financial services across Asset ClassesKnowledge of statistical methods, quant, or data analyticsExperience with AI-assisted software development tools and validating AI outputs for correctness, performance, and securityUnderstanding of responsible AI, data sensitivity, secure handling, resiliency and security expectationsProficient in the full Software Development Life Cycle and agile methods (CI/CD, security, resiliency)Practical cloud-native experienceleadership and mentorshipcross-functional collaborationproblem solving and critical thinkingPythonquant research and model developmentAI-assisted development tools