Staff Infrastructure Engineer - Data Streaming

Our Purpose

At SentinelOne, we are driven by a clear purpose: to give the advantage to those who secure our future. As AI reshapes how organizations build, operate, and innovate, the responsibility to protect them becomes more critical than ever. When you join SentinelOne, your work helps protect global enterprises, critical infrastructure, and the technologies shaping tomorrow. If you are motivated by meaningful challenges and want your impact to be real, measurable, and global, you will find purpose here.

About Us

SentinelOne is a company at the intersection of AI and security, pioneering a new operating model for cybersecurity. Our AI-native platform unifies protection across endpoint, cloud, identity, data, and AI systems to deliver autonomous detection and response with clarity and speed. By combining real-time analytics, intelligent automation, and a unified data foundation, we reduce noise, simplify complexity, and empower security teams to focus on what truly matters.

Our teams are builders, problem-solvers, and innovators committed to shaping the future of security. If you are excited to solve hard problems alongside talented, mission-driven people, we invite you to help us build a safer future for humanity.

What Are We Looking For?

We’re looking for people who are relentlessly curious and committed to continuous learning. AI is reshaping every function across our business, and we enable every team member, regardless of role or level, to build fluency in AI tools and concepts. Those who thrive here actively seek out new solutions, experiment thoughtfully, and apply what they learn to drive better, faster, smarter outcomes.

What Will You Do?

Primary responsibilities include:

• Lead the design and operation of distributed data services, including Kafka and Redis (self hosted), running at massive scale across Kubernetes clusters and multi-cloud environments.
• Unlock complete cloud portability for SentinelOne's services by building a highly automated, self-service infrastructure that can run seamlessly across AWS, GCP, and air-gapped on-prem environments.
• Manage data infrastructure supporting 5 or more PB/day ingestion, ensuring low-latency, high-throughput, and cost-effective operation at global scale.
• Consolidate and optimize multi-tenant Kafka clusters to reduce cost, improve resilience, and streamline operations.
• Drive Redis and Kafka lifecycle automation using GitOps principles (ArgoCD, Terraform), reducing operational toil and minimizing pager fatigue.
• Define and implement standards for observability, HA, backup, and DR of stateful workloads in Kubernetes.
• Partner with FinOps and engineering stakeholders to continuously optimize performance, cost, and operational overhead across data platform components.
• Own the end-to-end platform experience for mission-critical open-source systems, serving hundreds of product teams.
• Collaborate closely with teams in Europe and India (US Eastern Time Zone preferred due to these collaboration requirements), working with orchestration tools such as Kubernetes (EKS, GKE), Jenkins, GitHub Actions, ArgoCD, and Terraform.

What Skills and Knowledge Will You Bring?

Ideal candidates will have:

• 8 or more years of experience in infrastructure/platform engineering, with a proven track record of operating stateful distributed systems at scale.
• Deep hands-on experience with self hosted Kafka and Redis running in Kubernetes, including performance tuning, scaling, partitioning, persistence, and operator-based lifecycle management.
• Strong understanding of Kubernetes internals and best practices for managing both stateless and stateful workloads in production environments.
• Experience providing Database- or Messaging-as-a-Service (DBaaS/PaaS) for internal development teams or external customers.
• Exposure to multi-cloud environments with strong expertise in at least one major provider: AWS, GCP, or Azure.
• Experience with Infrastructure as Code and GitOps practices (Terraform, ArgoCD, Pulumi).
• Familiarity with advanced deployment strategies (blue-green, canary, rolling).
• Strong scripting or development skills (e.g., Python, Go, or similar).
• Solid understanding of CI/CD pipelines and workflow automation (GitHub Actions, Argo Workflows, etc.).