Jobs at Schonfeld

The Software Engineer will enhance the Business Analytics team's infrastructure through Python coding, automation, and reporting while collaborating with business stakeholders.

Design, build, and operate highly available reference/master data systems for a hedge fund. Lead architecture, cloud microservices, LLM/agentic solutions, and cross-functional projects while mentoring engineers and improving reliability, security, and performance.

Manage market data sourcing, licensing, and entitlements across global vendors. Support portfolio managers and oversee data compliance and usage tracking.

Provide legal support for portfolio manager onboarding/offboarding, draft and negotiate investment management and employment agreements, manage fund formation and capital development (side letters, placement agent agreements, product launches), assist on strategic/private equity/loan and regulatory matters, collaborate with internal stakeholders and outside counsel, and respond to investor queries.

You will design, implement, and improve AI-powered workflows while collaborating closely with product teams and stakeholders to enhance the firm's Agentic AI platform.

Senior Software Engineers will design, develop, and support applications for trade operational data, leading projects and providing Level 3 support globally.

The Full Stack Engineer will develop and enhance the firm's AI platform, focusing on UI and backend work using various technologies, and collaborate closely with product teams and stakeholders.

As a Software Engineer, you'll develop backend services and data pipelines, integrate AI solutions, and collaborate closely with investment professionals to enhance productivity and data utilization.

Lead Data Engineer at Schonfeld focuses on developing and advancing talent while leveraging proprietary technology for investment strategies, fostering a collaborative work environment.

Build and evolve an internal UI platform used by 100+ applications. Work full-stack on front-end, backend integration, API design, performance and observability. Contribute shared components, architecture improvements, testing, mentor juniors, and collaborate with product teams and stakeholders to deliver scalable, data-intensive, high-usability UI solutions.

The AI Data Engineer will design and implement data pipelines, build AI-optimized data infrastructure, ensure data quality, and collaborate with teams to support AI applications.

Manage full lifecycle recruiting for front-office roles (Quants, Strats, Risk, Technology). Partner with business stakeholders and search firms, source and engage candidates, run processes end-to-end, and ensure a best-in-class candidate experience while supporting broader hiring needs.

Coordinate recruitment activities for global offices: schedule interviews across time zones, manage ATS records, arrange candidate travel, liaise with hiring managers and agencies, compile recruitment reports, improve processes, and support diversity initiatives.

The Risk Manager will oversee risk assessments, develop strategies, monitor risks, and collaborate with teams on managing credit product risks.

Designs and maintains the enterprise AI knowledge library and role-based AI curriculum. Creates content, manages LMS/CMS, runs training events, tracks KPIs, and produces analytics dashboards. Partners with AI Technology and business units to drive adoption, run communications, support AI champions, and continuously improve training based on user feedback and metrics.

The Communications Associate will support global communications strategies, manage messaging, assist with events, and collaborate across teams to enhance engagement.