Required Skills & Experience:

Bachelor's degree (Masters Degree preferred) in Computer Science, Information Technology, or related fields
5+ years of experience in Cloud & AI
2+ years on Generative AI,
Experience in integrating AI/ML models into cloud solutions
Deep understanding of Azure services, including but not limited to Azure Virtual Machines, Azure Container Apps Environment, Azure Machine Learning, Azure Functions, and Azure Cognitive Services
Experience working with Generative AI Frameworks such as LangChain, LlamaIndex, etc
Hands-on experience with IaC tools such as Terraform, ARM templates, or Bicep

Nice to Have Skills & Experience:

Proven experience in DevOps practices, including setting up and managing CI/CD pipelines using GitHub Actions or Azure DevOps

Key Responsibilities:

Drive the design, development, and deployment of cloud-native Generative AI solutions on Azure.
Implement and maintain DevOps best practices, including CI/CD pipelines, Infrastructure as Code (IaC), and version control using GitHub or Azure DevOps.
Collaborate with data scientists, AI/ML teams, and business stakeholders to deploy and optimize AI models within cloud-native architectures, ensuring seamless integration and performance at scale.
Drive cloud architecture decisions in partnership with Enterprise Architecture, TechOps, and Cybersecurity functions, ensuring scalability, security, and cost efficiency
Build and manage CI/CD pipelines to streamline the deployment process and ensure rapid delivery of high-quality applications.
Advocate and implement Infrastructure as Code (IaC) to automate infrastructure provisioning, ensuring consistency across environments.
Collaborate closely with cross-functional teams, promoting a culture of teamwork and innovation.
Provide technical leadership, mentoring team members, and fostering a continuous learning environment.
Stay up to date with the latest trends in Azure services, AI technologies, and DevOps practices to recommend innovative solutions.

Cloud Engineer