About the role
Strength in Trust OneTrust’s mission is to enable innovation through the responsible use of data and AI. We believe that ensuring data is trusted shouldn’t slow teams down—it should accelerate what’s possible. This led us to develop the first technology platform for responsible data use in 2016. Today, with AI representing the latest and most impactful expansion of data yet, OneTrust is once again redefining what responsible innovation looks like. OneTrust, the AI‑Ready Governance Platform™, unifies regulatory intelligence, automation, and connected governance workflows so businesses can continue to move at the speed of AI while ensuring good governance to prevent data misuse at scale. Trusted by thousands of organizations worldwide, OneTrust is shaping the future where trusted data becomes a transformative force for business and society. The Challenge Own production services end-to-end, including reliability, scalability, and operational excellence Participate in on-call rotation and lead incident response Your Mission Engage and partner with various Engineering, Operations, and Product teams to design, deliver, and maintain a highly available and performant application platform. Collaborate with different functional groups to identify gaps, prioritize, and resolve issues Defining, implementing, and maintaining SLIs and SLOs aligned with customer experience. Design and instrument SLIs such as latency, error rates, and availability across critical services Manage and enforce error budgets to balance system reliability with product feature velocity. Improving alert quality by reducing noise and focusing on actionable, high-signal alerts Embed with product teams to review architectures and catch reliability risks early Share your knowledge and experience with the Engineering organization Share your findings with technical leadership and senior management Build scripts in python/bash/java or ruby for operational automation and incident response You Are A hands-on engineer familiar with running production services and providing understanding and solutions to appropriately monitor and automate those services. Your Experience Includes Bachelor's degree in computer science, Engineering, or related technical or business field 4+ yrs. of application development experience with Java or other equivalent language Experience with Spring environment . Experience in cloud-based infrastructure (Azure, AWS, GCP, etc.) Experience with the factors influencing performance of software applications at multiple layers (Database, network, CPU utilization, JVM tuning, memory analysis, thread management, query performance etc. ) An understanding of the importance of centralizing logging, metrics dashboards, and alerting. Able to talk about some of the tools used for these tasks A good understanding of databases (ideally SQL/NoSQL) Hands-on experience with observability tools (Datadog, Prometheus, Grafana, etc.) Familiarity with CI/CD pipelines and infrastructure-as-code (Terraform, Helm, jenkins, gitlab) Build and operate AI-assisted incident response systems (root cause analysis, log summarization, anomaly triage) Develop or integrate LLM-based tools to reduce MTTR and improve alert quality Apply machine learning techniques for anomaly detection, capacity prediction, or failure pattern analysis Experience deploying AI systems in production (not just experimentation) Familiarity with vector databases, embeddings, or RAG architectures for operational intelligence Strong understanding of prompt engineering and evaluation of LLM outputs in reliability workflow Kubernetes and container orchestration (EKS/AKS/GKE) Experience with distributed systems at scale Familiarity with service meshes and microservices architecture
