Jobs at Sift

Manage end-to-end contracting for customer, vendor, and partner agreements: draft, negotiate, and close standard commercial contracts; review AI-generated redlines; own contract automation, clause libraries, intake, repository, renewals, and reporting; collaborate with Sales, Deal Desk, Finance, Security, and Product; escalate complex or high-risk issues to counsel.

Serve as the technical liaison between customers, Customer Success, and product/engineering. Resolve complex technical issues, support the customer lifecycle, ensure ML model health, expand integrations, write scripts and queries to prove ROI, and automate internal and external processes to improve customer outcomes.

Build and deliver customer-facing features end-to-end across frontend and backend. Work with Customer Success and Product to prioritize requests and fix bugs. Contribute to backend services, maintain tooling and engineering practices, and move between multiple products and codebases while owning problems from request to release.

Build and deploy low-latency, production-grade ML models and end-to-end pipelines for fraud detection. Engineer high-frequency time-series features from massive event streams, maintain automated MLOps/CI-CD infrastructure, optimize runtime scoring performance across distributed systems, and collaborate with infrastructure, product, and data science teams to translate fraud signals into robust algorithmic solutions.

The role involves designing and delivering learning programs for internal teams and customers, focusing on effective training strategies and measurable outcomes, while managing the LMS and ensuring alignment with product goals.