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Actian

Offers data management and analytics platforms

Director of Platform Engineering

Engineering LeadershipPosted on Nov 10
Full-timeNo salary listed

About the Job

Requirements

  • At least 10 years of professional experience in Platform Engineering, DevOps, Infrastructure Engineering, or Site Reliability Engineering.
  • At least 3 years of direct engineering management experience.
  • Currently operating at Director of Platform Engineering, Director of DevOps, or an equivalent hands-on Director-level position.
  • Demonstrated experience building and scaling engineering teams, rather than exclusively managing established organisations.
  • A strong track record of delivering and operating production platforms within a technology product company.
  • The ability to combine technical leadership with hands-on engineering execution.
  • Deep, hands-on production experience with Kubernetes.
  • Strong infrastructure-as-code experience, particularly Terraform or Terragrunt.
  • Proven experience implementing GitOps and continuous integration and continuous delivery pipelines using Argo CD or comparable technologies.
  • Strong AWS expertise and practical experience designing cloud-portable architectures.
  • Demonstrated experience with self-hosted or on-premises enterprise software deployments.
  • Practical experience with SOC 2, ISO 27001, GDPR, and data residency requirements.
  • Experience with cloud cost optimisation, FinOps, and infrastructure efficiency.
  • Extensive practical use of AI coding assistants, development agents, and AI-driven automation.
  • Experience applying AI to engineering productivity and infrastructure operations.
  • Ability to identify, implement, and govern AI-driven operational workflows.
  • Clear communication and the ability to work across distributed international engineering teams.
  • Comfort working across US Eastern and Central European time zones, with at least four hours of daily overlap with both.

Responsibilities

  • Establish and lead the Platform Engineering organisation from the ground up.
  • Design and implement scalable, reliable platform services supporting the data catalog, knowledge graph, and integration APIs.
  • Define the architecture and engineering standards used across the organisation.
  • Establish clear ownership boundaries and effective collaboration with product engineering teams.
  • Design and deliver a cloud-agnostic deployment architecture across AWS, Azure or Google Cloud, and customer-managed on-premises and private-cloud environments.
  • Build and maintain Kubernetes-based infrastructure in production.
  • Own infrastructure as code using Terraform or Terragrunt and GitOps-based deployment using Argo CD or equivalent technologies.
  • Ensure reliable installation, upgrades, maintenance, and supportability across different customer environments.
  • Support restricted-network and air-gapped deployment scenarios where required.
  • Integrate AI agents into infrastructure operations, including incident triage, remediation, change validation, and reporting.
  • Use AI coding assistants and development agents extensively in daily engineering work.
  • Establish practical standards for AI-assisted engineering across the platform team.
  • Identify opportunities to replace traditional tools and operational processes with AI-driven automation.
  • Build infrastructure to support AI and machine-learning workloads, including model-serving environments and associated data services.
  • Ensure appropriate human oversight, security guardrails, and auditability for AI-driven operations.
  • Establish security and compliance practices supporting SOC 2 Type II, ISO 27001, and GDPR.
  • Ensure compliance with EU data residency and customer-specific security requirements.
  • Implement automated compliance evidence collection and audit readiness.
  • Establish observability, monitoring, incident management, and on-call practices.
  • Recruit, develop, and lead a high-performing Platform Engineering team.
  • Define the team's structure, responsibilities, processes, and engineering culture.
  • Remain technically involved while developing the team's capabilities and autonomy.
  • Work closely with the SVP of Engineering and other technical leaders to align platform strategy with business and product priorities.
  • Build and establish a high-performing Platform Engineering team with clear ownership and responsibilities.
  • Deliver a portable deployment architecture supporting AWS, at least one additional public cloud, and customer-managed infrastructure.
  • Establish infrastructure as code and GitOps delivery as standard engineering practices.
  • Introduce AI agents into operational workflows, with measurable reductions in manual effort and operational overhead.
  • Deliver scalable infrastructure foundations for the data catalog, knowledge graph, and integration APIs.
  • Automate compliance evidence collection and improve audit readiness.
  • Establish a reliable operating model covering observability, incident response, security, and cloud cost management.
  • Report directly to the SVP of Engineering and work closely with Product Engineering, Security, Customer Success, and Support.
  • Occasionally travel for team offsites and company-wide meetings as required.

Desired Qualifications

  • Experience with Azure or Google Cloud.
  • Experience with enterprise data platforms, data catalogues, metadata management, or graph databases.
  • Production experience across multiple cloud providers.
  • Experience with air-gapped and restricted-network deployments.
  • Infrastructure experience for AI and machine-learning workloads, model serving, vector databases, or graph data stores.
  • Experience with OpenTelemetry or comparable observability technologies.
  • Experience with privileged access management solutions such as StrongDM.

About the Company

Actian

Offers data management and analytics platforms

Actian provides data management and analytics tools that help businesses connect to data, analyze it, and act on insights. Its products include Avalanche, a fully managed hybrid cloud data warehouse; DataCloud for data integration; Actian X for operational analytics, integration, and monitoring; Vector for high‑performance analytics; and Zen for embedded and IoT databases. These tools connect to various data sources, process data in real time, and let users run queries and analyses to derive insights, with options for both on‑premises and cloud deployments. Actian differentiates itself through an integrated suite that spans data ingestion, storage, analytics, and monitoring across on‑premises, cloud, and edge/IoT environments, enabling real‑time insight across diverse data sets. Its goal is to help organizations turn data into faster, better decisions, improve customer outcomes, manage risk, and unlock new revenue opportunities.

Company size
501-1,000
Company stage
Series E
Total funding
$84.5M
Headquarters
Redwood City, CA
Founded
2005

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