Senior Staff DevOps Engineer — Data Discovery & AI Governance

We are hiring a Senior Staff DevOps Engineer to join our Detect & Discover (D&D) team. This team owns three product lines — Data Discovery, Privacy Automation, and AI Governance — serving thousands of enterprise customers across multi-cloud and on-premises environments. In this role, you will lead the infrastructure strategy for our Kubernetes-based on-premises platform and cloud deployments. This includes architecting automated worker node deployments for Azure Marketplace, AWS Marketplace, and GCP; driving container-hardening initiatives to systematically eliminate CVEs; and ensuring the reliability, scalability, and security of our distributed scanning and classification platform. You will act as a technical leader, mentoring engineers and collaborating closely with product security, engineering squads, and customer-facing teams.

Responsibilities

Architect and maintain production-grade Kubernetes platforms across cloud (AKS, EKS, GKE) and on-premises (K3s, microk8s) environments; Own the full lifecycle — cluster provisioning, upgrades, node pool management, and disaster recovery; Develop and maintain automation using Helm, ARM templates, BICEP, Terraform, and CloudFormation to streamline worker node provisioning on Azure Marketplace, AWS Marketplace, and GCP Marketplace; Reduce customer setup complexity so clients don't need advanced Kubernetes expertise on-site; Lead our container-hardening program by adopting secure base images for distributed components including Kafka, PostgreSQL, Elasticsearch, Temporal and Vault; Own the systematic reduction of CVEs flagged by Vulnerability Scanners; Maintain and improve CI/CD pipelines ensuring zero-downtime deployments, automated rollbacks, and full auditability; Drive GitOps practices, Improve DevEx and infrastructure-as-code across the team; Design monitoring, alerting, diagnostics, and self-healing capabilities using Datadog, Loki, Promtail; Ensure the platform is optimized for performance, logarithmic cost growth, and high-throughput scaling across thousands of tenant environments; Lead incident investigations, root cause analysis, and long-term remediation for production service interruptions; Participate in on-call rotation and drive systemic fixes to prevent recurrence; Mentor engineers, drive DevOps best practices across teams, and raise the technical bar for infrastructure engineering quality

Requirements

Bachelor's degree in Computer Science, Engineering, or a related technical field; 8+ years in DevOps, SRE, or Platform Engineering roles; Expert knowledge of Kubernetes, Helm, Linux, Docker, and networking; Strong working knowledge of Azure, AWS, and GCP, with specific depth in at least one; Proficiency in Go and/or Python, plus Bash/Shell scripting for infrastructure automation and integrations; Deep understanding of CI/CD pipelines (GitLab or similar), GitOps workflows, and infrastructure-as-code methodologies; Experience with PostgreSQL, Elasticsearch, and distributed messaging systems (Apache Kafka, NATS); Experience with security scanning, container image hardening, and vulnerability remediation in enterprise environments; Experience supporting enterprise production environments and handling customer escalations; Prior experience working in Agile/Scrum enterprise software development; Excellent verbal and written communication and technical leadership skills; A hands-on technical leader with strong analytical and problem-solving skills; Technically curious and self-motivated; A collaborative partner who works seamlessly with security teams, software developers, and product managers; Someone who thrives in ambiguous environments, takes ownership of complex technical challenges, and influences across teams without direct authority; An encouraging mentor who enjoys upskilling engineers and continuously improving reliability, automation, and customer experience

Nice to have

Experience building and publishing B2B enterprise software on Azure Marketplace, AWS Marketplace, or GCP Marketplace; Proven experience with Chainguard or other minimal, hardened container distributions for software supply chain security; Experience with on-premises enterprise software deployments (K3s, microk8s, airgapped environments); Familiarity with Temporal workflow orchestration or similar durable execution frameworks; Prior exposure to MLOps methodologies, including model versioning, pipeline auditability, and AI asset discovery; Experience with service meshes, Kubernetes operators, and AI-assisted operations

Benefits

comprehensive healthcare coverage; flexible PTO; equity RSUs; annual performance bonus opportunities; retirement account support; 14+ weeks of paid parental leave; career development opportunities; company-paid privacy certification exam fees; discretionary bonuses; commissions