Job description

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 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 Compensation: Annual salary range of USD $200,000 – $380,000, commensurate with experience. Why Join Us • Impact at Scale: Work on fraud detection systems processing billions of events daily. • Cutting-Edge Tech: Push the frontier in streaming, agentic AI, and big data infrastructure. • Career Growth: Lead a high-impact team with opportunities to shape technical direction and grow into senior leadership.

Requirements

Must-haves

DataVisor is a next-generation SaaS company that protects the world’s largest enterprises from fraud and money laundering.
Join us and help push the boundaries of what’s possible in fraud detection.
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 inclusive, high-accountability culture that supports growth, ownership, and innovation.
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
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

Nice-to-haves

BS degree in Computer Science or related field required; MS/PhD preferred
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 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

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimachine learningmljavapythonllmsql

Platform: workable
Effort: medium

Benefits

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Vision