Director of Engineering

DataVisor is a next-generation SaaS company that protects the world’s largest enterprises from fraud and money laundering. Our award-winning AI decision platform combines industry-leading unsupervised machine learning (UML) with advanced supervised models to stop fraudulent activity across financial transactions, mobile growth, social networks, and e-commerce. We partner with leading global brands, delivering solutions built on top of our highly scalable platform.Behind these innovations is a world-class team of experts in big data, security, and distributed infrastructure, thriving in a culture that is open, collaborative, and results-driven. Join us and help push the boundaries of what’s possible in fraud detection. Role Summary We are seeking a Director of Engineering to lead our Platform Engineering team. This team is at the heart of DataVisor’s detection capabilities, building the AI-based fraud and risk decision platform that powers real-time and batch unified decisioning at enterprise scale. You will lead and grow a high-performing engineering organization, set technical direction, and drive execution across a critical part of DataVisor’s platform. Working closely with product, data science, infrastructure, and executive leadership, you will help shape our next-generation AI agent driven infrastructure and enable our customers to detect and stop complex fraud patterns in real time. What You’ll Do Define Strategy & Roadmap: Set the technical vision and execution roadmap for the Platform Engineering team in alignment with company priorities and long-term product strategy. Lead at Scale: Build, manage, coach, and grow a high-performing team of engineers and engineering leaders, fostering technical excellence, strong execution, and career development. Architect & Deliver: Oversee the design and delivery of a large-scale, AI-based fraud and risk decision platform that supports enterprise-grade real-time and batch decisioning. Drive Innovation in Fraud Detection: Partner across engineering and data science to apply unsupervised, supervised, and agentic AI methods to uncover and stop fraudulent behavior. Unify Decisioning: Lead the development of a real-time and batch unified decision platform that powers enterprise-scale fraud prevention. Scale Infrastructure: Guide the evolution of distributed, real-time data systems for low-latency, highly reliable decisioning. Leverage Big Data: Drive adoption and effective use of Spark, Flink, Cassandra, Kafka, and related technologies to support high-throughput ML and data pipelines. Partner Cross-Functionally: Work closely with product, infrastructure, security, customer-facing teams, and executive leadership to align engineering delivery with business needs. Raise the Bar: Establish strong engineering processes, operational rigor, architecture reviews, and high-quality development practices across the organization. Hire & Develop Talent: Attract top engineering talent and build an…