Senior Software Engineer - Next Gen DLP

Cato Networks is the converged network and security cloud for the AI era. As AI reshapes cybersecurity, enterprises face a dual challenge: unlocking AI's potential while defending against AI-driven attacks. Cato addresses both through a unified, cloud-native platform, providing the visibility and context to prioritize risks and stop threats in real time across users, applications, data, and AI agents. Join us as we scale: take on ambitious technological challenges and shape the next generation of enterprise security at a company trusted by thousands of organizations worldwide. About the role We're building a new product at the intersection of AI and data security - with startup speed, real ownership and Cato's enterprise scale behind us. Join Cato DataSec to turn complex security data into a product that helps enterprises adopt AI with confidence. This is an opportunity to shape a product from its earliest stages: solve open engineering problems, make architectural decisions and get working software into customers' hands. You'll build on Cato's global SASE cloud, with real customers and real data from day one. The engineering spans distributed systems, high-volume data processing, advanced analytics and the frontend experience that brings them together. The challenge is turning fragmented signals into intelligence that customers can act on - quickly, reliably and at scale. What you'll do Ship complete features. Own capabilities end to end, from data pipelines and backend services through APIs and frontend implementation, rollout and iteration. Find connections in complex data. Develop correlation and analytical capabilities that turn large volumes of security events into meaningful insights. Build for scale. Design and operate streaming and batch pipelines, balancing throughput, latency, correctness and cost. Shape the architecture. Make decisions across backend services, data processing and analytics, and validate them against production behaviour. Stay close to the customer problem. Work with Product, Research, Data Science and security teams to turn emerging needs into shipped capabilities. Own what you ship. Investigate issues, improve performance and reliability, and keep raising the quality of the product. Our stack includes Java/Spring Boot, Kafka, Spark/Flink, ClickHouse/Athena and AWS. Who we're looking for You've built something substantial and stayed with it after launch. You can explain the decisions you made, the constraints you worked around and what changed once real users arrived. You've taken an unclear problem, worked out a practical approach and shipped a useful first version. You make progress without waiting for every detail to be specified, and you know which assumptions need testing before moving ahead. You want to remain hands-on across the product: writing backend code, building frontend flows and owning production outcomes. You follow a feature through to a usable customer experience, including work outside your strongest area. Your background might be a startup, a large-scale platform, a technology unit or research. Math, engineering and other non-CS paths are welcome. What you've built - and how you approached it - matters more than a perfect CV. Requirements 5+ years of hands-on backend or software engineering, including production delivery. Built and operated a data-intensive system, pipeline or analytics service. Production experience with distributed systems and event-streaming infrastructure. Shipped a user-facing feature end to end, with hands-on contributions to both backend and frontend implementation. Can explain technical tradeoffs using concrete examples involving scale, reliability, performance or data correctness. Can walk through a production issue you diagnosed and how you verified the fix. Advantages Correlation, similarity or entity resolution: matching, identity graphs or near-duplicate detection. Data or AI security: DLP, CASB, DSPM, insider risk or AI-security systems. Spark plus ClickHouse/Athena: pipeline development and analytical performance. Flink or systems processing billions of events per day. AWS, privacy engineering or production ML capabilities. Startup, founding-team or zero-to-one product experience. Why join Build at an early stage with the reach of an established security platform. You'll influence the architecture, work through problems without a ready-made playbook and see your decisions tested by enterprise use. If you want your next role to include "built it from scratch" and "owned it in production," we'd like to hear from you.