AI/ML applications for workflow automation, data validation, and operational excellence
Platform Over People: Prioritizes building robust platforms and automation over relying on individual heroic efforts, enabling sustainable and scalable growth
AI-First, Human-in-the-Loop: Embraces AI-driven solutions as a default for efficiency and scale, while keeping expert human judgment in critical loops to ensure quality and trust
Deep Co-Ownership with PMG: Fosters a culture of partnership with the Portfolio Management Group, aligning closely on priorities, sharing roadmaps and KPIs, and co-owning outcomes to ensure the platform truly meets investment teams' needs
API-first platform design and developer experience best practices
Standardization Everywhere: Drives consistency in tools, processes, and data across the board, reducing complexity and improving interoperability and maintainability
For New York, NY Only the salary range for this position is USD$225,000.00 - USD$285,000.00
Proven track record of driving innovation, navigating ambiguity, and delivering measurable outcomes at scale
An advanced degree is a plus
Ability to influence and align product teams, platform/infrastructure teams, and governance bodies around a common vision and roadmap
Single Front Door: Advocates for a unified user experience where researchers and stakeholders have one intuitive portal for all their needs, simplifying access and support
Strategic Engineering Leadership: Proven experience leading large-scale engineering organizations through product transformation initiatives (e.g., platform modernization, cloud migration, operating model changes). Demonstrated success in setting vision and executing across complex, multi-year technology programs
Self-Service as the Default: Champions self-service capabilities, empowering users to accomplish tasks independently (from data ingestion to model deployment) without bespoke engineering work
Demonstrated strength in partnership-building and cross-functional collaboration
Bachelor's degree in Computer Science, Engineering, or a related field; or equivalent practical experience
Alpha generation workflows or closely related quantitative research processes in finance/investments
Cloud technologies and cloud-native architectural patterns (e.g., microservices, containerization, distributed computing e.g. Ray)
Modern stack knowledge and skills - e.g. Python, Polars, Ray, MLFlow or equivalent technology