Senior Staff DevOps Engineer — Data Discovery & AI Governance

The Mission

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

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.

Your Mission

Kubernetes Platform Architecture: 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.

Deployment Automation & Marketplace Publishing: Develop and maintain automation using Helm, ARM templates, BICEP, Terraform, and CloudFormation to streamline worker node provisioning on Azure Marketplace, AWS Marketplace, and Reduce customer setup complexity so clients don't need advanced Kubernetes expertise on-site.

Container Hardening & Vulnerability Management: 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.

CI/CD & Release Engineering: 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.

Observability & Platform Reliability: 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.

Incident Response & Production Support: 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.

Mentorship & Technical Leadership: Mentor engineers, drive DevOps best practices across teams, and raise the technical bar for infrastructure engineering quality.

You Are

A hands-on technical leader with strong analytical and problem-solving skills and a passion for high-quality infrastructure engineering.

Technically curious and self-motivated, able to self-teach new technologies and prioritize complex tasks in a fast-paced environment.

A collaborative partner who works seamlessly with security teams, software developers, and product managers to drive alignment on infrastructure standards.

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.

Your Experience Includes

Education: Bachelor's degree in Computer Science, Engineering, or a related technical field.

Experience: 8+ years in DevOps, SRE, or Platform Engineering roles.

Container Orchestration: Expert knowledge of Kubernetes, Helm, Linux, Docker, and networking

Multi-Cloud Platforms: Strong working knowledge of Azure, AWS, and GCP, with specific depth in at least one.

Automation & Scripting: Proficiency in Go and/or Python, plus Bash/Shell scripting for infrastructure automation and integrations.

CI/CD & GitOps: Deep understanding of CI/CD pipelines (GitLab or similar), GitOps workflows, and infrastructure-as-code methodologies.

Databases & Messaging: Experience with PostgreSQL, Elasticsearch, and distributed messaging systems (Apache Kafka, NATS).

Security & Compliance: Experience with security scanning, container image hardening, and vulnerability remediation in enterprise environments.

Production Operations: Experience supporting enterprise production environments and handling customer escalations.

Methodologies: Prior experience working in Agile/Scrum enterprise software development.

Communication: Excellent verbal and written communication and technical leadership skills.

Extra Awesome

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.

For California, Colorado, Connecticut, Nevada, New York, Rhode Island, and Washington-based candidates: the annual base pay range for this role is listed below. Within this range, individual pay is determined by several factors, including location, job-related skills, work experience, and relevant education and/or training. This role may also be eligible for discretionary bonuses, equity, and/or commissions, as well as benefits.

Salary Range

$165,000—$247,500 USD