Software Engineering Manager - Platform Team at DataVisor

Mountain View, California, United States -

Full Time

Start Date

Immediate

Expiry Date

22 Dec, 25

Salary

0.0

Posted On

23 Sep, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Software Engineering, AI, Machine Learning, Fraud Detection, Big Data, Java, C++, Python, System Design, Architecture, Team Management, Mentoring, Distributed Systems, Real-Time Data Processing, SQL, Spark

Industry

Software Development

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 Software Engineering Manager 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 manage a talented team of engineers while also contributing to the design and development of our next-generation AI agent driven infrastructure. Together, you’ll enable our customers to detect and stop complex fraud patterns in real time. What You’ll Do Design & Build: Architect and deliver a large-scale, AI-based fraud and risk decision platform. Innovate in Fraud Detection: Apply unsupervised, supervised, and agentic AI methods to uncover and stop fraudulent behavior. Unify Decisioning: Drive the development of a real-time and batch unified decision platform that powers enterprise-scale fraud prevention. Scale Infrastructure: Build and optimize distributed, real-time data systems for low-latency decisioning. Leverage Big Data: Utilize Spark, Flink, Cassandra, and related technologies to enable high-throughput ML pipelines. Lead & Mentor: Manage, coach, and grow a team of engineers, fostering technical excellence and professional development. BS degree in Computer Science or related field required; MS/PhD preferred Fluent in Java or C++ programming, with knowledge of Python; hands-on in coding, system design, and architecture 3+ years of experience leading or managing teams 8+ years of software development experience Solid understanding of AI/ML concepts (unsupervised, supervised, and emerging approaches such as agentic AI); experience applying ML in production systems is a strong plus 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 Exposure to test-driven development and high-quality engineering practices Excellent oral and written communication skills Strong team spirit and collaboration mindset 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.

Responsibilities

Lead the Platform Engineering team to design and build a large-scale AI-based fraud and risk decision platform. Manage a team of engineers while contributing to the development of infrastructure that enables real-time fraud detection.