About Skai

Skai (formerly Kenshoo) is a leading omnichannel marketing platform that leverages advanced AI and machine learning to combine data intelligence with performance media, enabling smarter decision-making, increased efficiency, and maximized returns for businesses around the world. Its partners include Google, Meta, Amazon, Microsoft, and more. Approximately $10 billion in ad spending is managed on the Skai platform every year.

Established in 2006, we’re 700 employees strong.

We work hybrid, with a great home/office mix.

What will you do?

As the Senior DevOps Architect, you will own the architectural direction of Skai’s cloud infrastructure, engineering platforms, and developer experience across our Cloud and DevEx groups.

Combining infrastructure expertise with hands-on software engineering, you will turn business and engineering needs into technical roadmaps and production solutions, including AI services and agents for internal and external-facing systems.

As part of your work you will be responsible for:

• Own the technical roadmap and architecture across DevOps and DevEx, establish shared standards, and lead initiatives from design to production through hands-on implementation.
• Architect scalable, secure, and resilient cloud infrastructure, covering Kubernetes, networking, infrastructure as code, and modernization.
• Design shared platforms and self-service workflows that simplify development, CI/CD, deployment, and troubleshooting.
• Define architectural standards for observability, availability, disaster recovery, and capacity planning.
• Architect and contribute to production AI services and agents, including system integration, evaluation, security, and reliable operation.
• Align priorities with R&D, Product, and Security, resolve cross-team dependencies, and mentor engineers and technical leads.

• 3+ years experience as DevOps Architect, owning architecture and leading technical initiatives across multiple teams, with 8+ years of overall experience in infrastructure, DevOps, platform engineering, or software engineering.
• 5+ years of hands-on programming experience in languages such as Python, Go, or Java, including designing and maintaining production services, APIs, or shared engineering tools.
• Demonstrated experience architecting distributed production systems, including defining service boundaries, selecting technologies, documenting trade-offs, and leading implementation and migration.
• Deep expertise in at least one major cloud platform AWS, GCP, or Azure and hands-on experience with Kubernetes, infrastructure as code tools such as Terraform, and CI/CD or GitOps tooling such as Jenkins, GitHub Actions, or Argo CD.
• Experience designing developer platforms, reusable infrastructure components, and self-service workflows adopted by multiple engineering teams.
• Strong understanding of networking, cloud security, observability, high availability, and disaster recovery, supported by experience operating and troubleshooting production systems.
• Proven experience building and deploying AI services and agents to production, including model integration, orchestration, tool calling, evaluation, and integration with internal or external systems.
• Experience defining technical requirements with stakeholders, presenting architectural proposals, and leading cross-team decisions through implementation and adoption.

Advantages:

• Experience designing and operating data infrastructure, including streaming, workflow orchestration, and large-scale processing with technologies such as Kafka, Airflow, or Spark.
• Experience with database, data warehouse, or data lake architecture and operations, including performance tuning, capacity planning, backup and recovery, and data reliability.
• Experience building shared AI platforms or delivering both internal automation agents and customer-facing AI services.