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.

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.

• →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 inclusive, high-accountability culture that supports growth, ownership, and innovation.

• BS degree in Computer Science or related field required; MS/PhD preferred
• 10+ years of software development experience, including substantial experience leading engineering teams and organizations
• 5+ years of experience managing teams, with demonstrated success leading senior engineers and/or engineering managers
• Fluent in Java or C++ programming, with knowledge of Python; strong background in system design, architecture, and scalable distributed systems
• Solid understanding of AI/ML concepts (unsupervised, supervised, and emerging approaches such as agentic AI); experience applying ML in production systems is strongly preferred
• Familiarity with modern AI systems, including LLM-powered applications, model evaluation, prompt-driven workflows, and agent-based system design
• Experience leading engineering teams that build AI-enabled products, data-intensive platforms, or ML infrastructure is a strong plus
• Experience leading large-scale platform or infrastructure initiatives in high-growth or technically complex environments
• Familiarity with relational databases, SQL, and ORM frameworks (JPA, Hibernate) is a plus
• Experience with big data technologies (Cassandra, Flink, Spark, Kafka) preferred
• Knowledge of the Spring Framework is a plus
• Strong track record of operational excellence, cross-functional collaboration, and execution against ambitious goals
• Excellent oral and written communication skills, including the ability to influence across technical and business audiences
• Strong team spirit, sound judgment, and a leadership mindset grounded in collaboration and accountability