Skai
Skai
Skai एक B2B मार्केटिंग टेक्नोलॉजी कंपनी है, जो ब्रांडों को कॉमर्स मीडिया में विज्ञापन प्रबंधित करने में मदद करती है। इसका ओम्नीचैनल प्लेटफ़ॉर्म रिटेल मीडिया नेटवर्क, सर्च और सोशल विज्ञापन को एक ही इंटरफ़ेस में लाता है, जिससे मार्केटरों को कैंपेन के प्रदर्शन और निवेश का समेकित दृष्टिकोण मिलता है। AI-संचालित टूल विज्ञापन डेटा को उपयोगी रणनीतियों में बदलते हैं, जिससे टीमें मीडिया कार्यक्रमों को बेहतर बना सकती हैं, बिखराव कम कर सकती हैं और डिजिटल कॉमर्स चैनलों में ब्रांड वृद्धि को समर्थन दे सकती हैं।

Senior DevOps Architect at Skai — Hybrid Israel

Lead DevOps and developer experience architecture for Skai’s AI-powered omnichannel marketing platform. Shape cloud infrastructure, self-service engineering platforms, and reliable production AI services across teams.

विवरण

  • Own the DevOps and developer experience architecture roadmap.
  • Set shared engineering standards and guide initiatives from design to production through hands-on delivery.
  • Design scalable, secure, resilient cloud infrastructure across Kubernetes, networking, infrastructure as code, and modernization.
  • Build shared platforms and self-service workflows for development, CI/CD, deployment, and production troubleshooting.
  • Establish architecture standards for observability, availability, disaster recovery, and capacity planning.
  • Design and help deliver production AI services and agents, including integration, evaluation, security, and operational reliability.
  • Coordinate priorities across R&D, Product, and Security.
  • Manage cross-team dependencies while mentoring engineers and technical leads.

आवश्यकताएँ

  • At least 3 years as a DevOps Architect, owning architecture and leading technical initiatives across multiple teams.
  • At least 8 years of experience in infrastructure, DevOps, platform engineering, or software engineering.
  • At least 5 years of hands-on programming experience with Python, Go, Java, or comparable languages.
  • Experience designing and maintaining production services, APIs, or shared engineering tools.
  • Experience architecting distributed production systems, defining service boundaries, evaluating technologies, documenting trade-offs, and leading implementation and migration.
  • Deep expertise in at least one major cloud platform: AWS, GCP, or Azure.
  • Hands-on experience with Kubernetes, Terraform or comparable infrastructure-as-code tools, and CI/CD or GitOps platforms such as Jenkins, GitHub Actions, or Argo CD.
  • Experience creating developer platforms, reusable infrastructure components, and self-service workflows used by multiple engineering teams.
  • Strong knowledge of networking, cloud security, observability, high availability, and disaster recovery.
  • Experience operating and troubleshooting production systems.
  • Demonstrated experience taking AI services and agents into production, including model integration, orchestration, tool calling, evaluation, and connections to internal or external systems.
  • Experience gathering technical requirements, presenting architecture proposals, and guiding cross-team decisions through implementation and adoption.
  • Experience designing and operating data infrastructure with Kafka, Airflow, Spark, or similar technologies is an advantage.
  • Experience with database, data warehouse, or data lake architecture and operations—including performance tuning, capacity planning, backup and recovery, and data reliability—is an advantage.
  • Experience building shared AI platforms or delivering internal automation agents and customer-facing AI services is an advantage.

लाभ

  • Hybrid work combining home and office work.

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