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Senior DevOps Engineer, AI4ALL

Responsibilities

  • Deploy and maintain secure cloud infrastructure primarily on GCP (Google Cloud Platform) and AWS, ensuring seamless integration between services.
  • Manage and optimize GKE (Google Kubernetes Engine) clusters for high-availability AI applications and microservices.
  • Infrastructure as Code: Build and enforce Terraform strategies to provision and manage infrastructure, ensuring environments are reproducible and version-controlled.
  • CI/CD & Software Verification: Design and implement advanced CI/CD workflows using GitHub Actions, moving beyond simple deployments to create intelligent automation.
  • Build robust verification pipelines that include automated testing, linting, security scanning, and quality gates before production release.
  • Streamline the release process for backend and frontend applications, ensuring "one-click" reliability.
  • Oversee the deployment, maintenance, and backup strategies for databases.
  • Implement comprehensive monitoring and logging solutions (Prometheus, Grafana, Cloud Ops, Cloud Monitoring) to ensure system health, performance, and rapid incident response.
  • Implement security best practices (IAM, VPC configuration, encryption) to protect sensitive AI data and intellectual property.

Qualifications

Education & Experience

  • B.Sc. or M.Sc. in Computer Science, Computer Engineering, or a related technical field.
  • 5+ years of relevant experience in DevOps, Cloud Engineering, or Site Reliability Engineering (SRE).
  • Proven experience acting as a Senior or Lead engineer, guiding architectural decisions.

Technical Requirements

  • Advanced hands-on experience with GCP (specifically GKE, VPC, IAM) and a working knowledge of AWS.
  • Proven ability to design and implement robust, scalable, and secure cloud architectures.
  • Mastery of Docker and Kubernetes administration.
  • Strong proficiency in Terraform.
  • Expert knowledge of GitHub Actions for building, test, build, and deploy pipelines.
  • Experience managing PostgreSQL and ClickHouse databases.
  • Deep understanding of Linux System Administration.
  • Experience with AI/ML lifecycle tools (e.g., Kubeflow, MLflow, Vertex AI).
  • Strong proficiency in Python and Bash scripting.
  • Familiarity with DevSecOps tools and practices.
  • Bonus: Official GCP Certifications (e.g., Professional Cloud Architect, Professional Cloud DevOps Engineer) and Kubernetes Certifications (e.g., CKA, CKAD, CKS) are highly preferred.
  • Bonus: Knowledge of Javascript/Node.js is a strong plus.

Soft Skills & Mindset

  • Ability to design long-term solutions rather than quick fixes.
  • Excellent ability to explain complex cloud concepts to Data Scientists and business stakeholders.
  • Comfortable working in a fast-paced environment with evolving requirements.
  • Fluent English is a must.

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