Cloud DevOps Engineer

Artemis Industries: As a leading-edge startup headquartered in Cyprus, we deliver innovative AI-driven solutions tailored to address the unique business challenges and aspirations of our customers. Our offerings span the entire development cycle, using state-of-the-art technologies and rigorous quality assurance to ensure performance, security, reliability, and scalability across various industry verticals, including agriculture, tourism, and financial services.

At Artemis Industries, we value motivated individuals who thrive in a collaborative team environment. We encourage our teams to achieve results and maximize their potential.

We are looking for a Cloud DevOps Engineer to work side-by-side with our global development team, ensuring seamless deployment and operation of our cloud-based solutions. This is a cutting edge product helping our customers create the next generation of their financial services compliance software based on generative AI technology.

Key Responsibilities:

• Kubernetes Cluster Management: Manage and deploy Kubernetes clusters across on-premises, multi-cloud, and edge environments using Azure Arc. Ensure consistent operations and governance for hybrid Kubernetes setups.
• CI/CD Pipeline Automation: Design and implement CI/CD pipelines using GitHub Actions to automate the deployment and operation of cloud-based applications. Ensure efficient and reliable deployment processes.
• GitOps Implementation: Implement GitOps practices to manage infrastructure and application configurations as code. Use tools like Flux or Argo CD to automate deployments and maintain system consistency.
• Infrastructure as Code (IaC): Build and manage Kubernetes clusters in both Azure and private cloud environments using BICEP, ARM templates, and Terraform. Automate infrastructure provisioning and management to ensure scalable and resilient deployments.
• Python and Flask Development: Develop and deploy machine learning models using Python. Build and deploy RESTful APIs in a cloud-native microservices architecture using Flask.
• Cloud-Native Microservices Architecture: Design and implement cloud-native microservices using containerization technologies (e.g., Docker, Kubernetes) to ensure scalable and resilient deployments.
• MLOps Practices: Work with the Artemis Industries data science team to define and apply MLOps practices to automate and streamline the machine learning lifecycle, including continuous integration and deployment (CI/CD) of ML models, monitoring, and governance.

جميع الحقوق محفوظة لموقع جوبس.

Skills and Experience:

• Azure Arc and Hybrid Kubernetes: Proficient in managing and deploying Kubernetes clusters across on-premises, multi-cloud, and edge environments using Azure Arc. Experience with hybrid Kubernetes setups to ensure consistent operations and governance.
• GitHub Enterprise and Actions: Strong experience with GitHub Enterprise for source code management and collaboration. Skilled in using GitHub Actions to automate CI/CD pipelines, ensuring efficient and reliable deployment processes.
• GitOps: Expertise in implementing GitOps practices to manage infrastructure and application configurations as code. Familiarity with tools like Flux or Argo CD to automate deployments and maintain system consistency.
• Infrastructure as Code (IaC): Proficient in using BICEP, ARM templates, and Terraform to build and manage Kubernetes clusters in both Azure and private cloud environments. Experience in automating infrastructure provisioning and management to ensure scalable and resilient deployments.
• Python and Flask: Strong proficiency in Python for developing and deploying machine learning models. Experience with Flask for building and deploying RESTful APIs in a cloud-native microservices architecture.
• Cloud-Native Microservices Architecture: Expertise in designing and implementing cloud-native microservices using containerization technologies (e.g., Docker, Kubernetes) to ensure scalable and resilient deployments.
• MLOps: Familiar with MLOps practices to automate and streamline the machine learning lifecycle, including continuous integration and deployment (CI/CD) of ML models, monitoring, and governance.
• Collaboration and Communication: Strong collaboration skills to work effectively with cross-functional teams, including data scientists, engineers, and product managers across multiple time zones and geographies. Excellent communication skills to articulate technical concepts and results to non-technical stakeholders.
• Programming Languages and Tools: Python, C#, Java, Semantic Kernel, LangChain

Qualifications:

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Proven experience in Python development, particularly in AI and machine learning applications.
• Strong knowledge of machine learning algorithms and frameworks.
• Experience with cloud platforms, preferably Microsoft Azure.
• Excellent problem-solving skills.
• Fluent in English for oral and written business communications.
• Ability to work in a fast-paced, dynamic environment.
• Experience with Kubernetes and containerization technologies.
• Proficiency in using Infrastructure as Code (IaC) tools such as BICEP, ARM templates, and Terraform.
• Familiarity with GitOps practices and tools like Flux or Argo CD.

Strong collaboration skills to work effectively with cross-functional teams across multiple time zones and geographies.

Interested and qualified applicants should send their C.V. and a cover letter to [email protected] ASAP.