Sr Software Engineer - GoLang , Linux , Distributed sys.

<div class="content-intro"><h3>About Us</h3> <p>At SentinelOne, we’re redefining cybersecurity by pushing the limits of what’s possible—leveraging AI-powered, data-driven innovation to stay ahead of tomorrow’s threats.</p> <p>From building industry-leading products to cultivating an exceptional company culture, our core values guide everything we do. We’re looking for passionate individuals who thrive in collaborative environments and are eager to drive impact. If you’re excited about solving complex challenges in bold, innovative ways, we’d love to connect with you.</p></div><h3><strong>What Are We Looking For?</strong></h3> <p>SentinelOne is seeking a Senior Software Engineer to join the Observo AI team in India, our cutting-edge AI-driven data pipeline optimization platform. This role will be responsible for designing, developing, and scaling high-performance systems that process massive volumes of telemetry data while reducing costs and improving insights for enterprise customers.</p> <p>We're looking for someone who values simplicity over complexity, who has experience with distributed systems at scale, and who brings thoughtful skepticism to technical decisions. You should be the kind of engineer who enjoys tackling challenging technical problems—whether that's contributing to open source, exploring distributed systems concepts, or deepening your understanding of database internals.</p> <p>This role is part of the Observo AI engineering organization and offers excellent opportunities for technical growth while contributing to our global engineering efforts. This is a hybrid role with 3 days in our Bengaluru office.</p> <h3><strong>What Will You Do?</strong></h3> <ul> <li>Design and implement scalable, high-performance data processing pipelines capable of handling petabyte-scale telemetry data (logs, metrics, traces)</li> <li>Build and optimize ML-driven data routing, filtering, and transformation engines to reduce customer data volumes by 80%+ while preserving critical insights</li> <li>Develop real-time analytics and anomaly detection systems using advanced machine learning techniques and large language models</li> <li>Build cloud-native microservices and APIs that integrate seamlessly with major observability platforms (Splunk, Elastic, Datadog, New Relic)</li> <li>Implement robust systems involving transactional queues, databases, and data processing pipelines</li> <li>Participate in technical design discussions with a focus on practical, maintainable solutions</li> <li>Collaborate with Product, Data Science, and DevOps teams across global time zones to translate customer requirements into technical solutions</li> <li>Optimize system performance, cost efficiency, and reliability through continuous profiling, testing, and infrastructure improvements</li> <li>Contribute to engineering culture through code reviews, testing best practices, and knowledge sharing</li> <li>Stay current with emerging technologies in AI/ML, data engineering, and observability</li> </ul> <h3><strong>What Skills and Knowledge Should You Bring?</strong></h3> <p><strong>Experience Track Record</strong></p> <ul> <li>4+ years of software engineering experience with demonstrated growth and depth in your roles, particularly in distributed systems, data engineering, or backend infrastructure</li> <li>Track record of building and shipping production systems in high-growth environments</li> <li>Experience working with complex systems and developing intuition for potential failure modes</li> <li>Understanding that simplicity and maintainability are critical for long-term success</li> </ul> <p><strong>Technical Expertise</strong></p> <ul> <li>Strong proficiency in Go, Rust, or Java with solid understanding of system design patterns and software architecture principles</li> <li>Experience with cloud platforms (AWS, GCP, Azure) and container orchestration technologies (Kubernetes, Docker)</li> <li>Experience building data pipelines using technologies like Ap ... (truncated, view full listing at source)