Director of Platform Engineering [gn] Data Intelligence Platform

Job summary

This hands-on director will build and lead a platform engineering team that enables a data intelligence platform to deploy, operate, and pass audits across AWS, another public cloud, and customer-managed private-cloud and on-premises environments. The role combines platform services for a data catalog, knowledge graph, and integration APIs with Kubernetes, Terraform/Terragrunt, GitOps, CI/CD, compliance automation, FinOps, and observability. It also includes building infrastructure for AI and ML workloads and using guarded AI agents to automate operations.

Benefits

Qualifications

• At least 10 years of experience in platform engineering, infrastructure, DevOps, or SRE, including at least 3 years managing engineers.
• Experience building or scaling an engineering team.
• Experience shipping on-premises or self-hosted software for customers to install and operate.
• Production experience with Kubernetes, Terraform or Terragrunt, and GitOps delivery using Argo CD or similar tools.
• Strong AWS experience and the ability to design for portability across cloud providers.
• Experience operating systems under SOC 2, ISO 27001, and GDPR controls, including data residency requirements.
• Experience managing cloud costs and communicating cost trade-offs to engineering and business leaders.
• Extensive use of AI to accelerate engineering work.
• Clear written communication for collaboration across US and EU time zones.

Responsibilities

• Build, lead, hire, and grow a platform engineering team.
• Design platform services, write infrastructure code, and establish engineering standards.
• Deliver cloud-agnostic deployments across AWS, another public cloud, and customer on-premises and private-cloud environments.
• Own the internal developer platform, CI/CD, and GitOps delivery.
• Automate security operations and compliance evidence for SOC 2 Type II, ISO 27001, and GDPR, including EU data residency.
• Manage cloud costs and establish FinOps practices.
• Build infrastructure for platform AI and ML workloads.
• Own observability, reliability, incident response, and the team's on-call rotation.
• Build and operate AI agents for infrastructure tasks with human approval for high-risk changes and audit trails.
• Establish scalable infrastructure for data catalog, knowledge graph, and integration API services.

Skills

Work schedule

Travel

Industry

Relocation