GenAI Cloud Engineer/MLOps Engineer Contract

We are seeking a highly skilled Senior Cloud Engineer with expertise in provisioning AI resources on the Azure platform (or Google Cloud Platform). The ideal candidate will have extensive experience in deploying and managing AI/ML solutions while adhering to enterprise security standards. Additionally, familiarity with GenAI architecture and other cloud providers’ AI/ML offerings is highly desirable.

Key Responsibilities:

• Provision and automate cloud infrastructure/platforms to support AI resources on Azure (or other cloud providers like Google Cloud Platform), including AI/ML Studio, Cognitive APIs, Azure Open AI, API Manager, Vector Store, Azure Databricks, and CPU/GPU compute clusters.
• Provide platform engineering support for AI/ML solutions, including IAAS, PAAS, and SAAS enablement.
• Ensure scalability, availability, and reliability of AI/ML solutions through robust architecture and infrastructure design.
• Implement multi-region deployments to optimize performance and redundancy.
• Collaborate with cross-functional teams to define and implement infrastructure for GenAI architecture principles, including RAG, LLM’s, and data pipelines.
• Implement and maintain service reliability engineering (SRE) practices to enhance system resilience and availability.
• Stay up to date with the latest advancements in cloud technologies, AI/ML algorithms, and security best practices.
• Communicate effectively with stakeholders to gather requirements, provide updates, and address technical concerns.
• Provide some basic samples to the teams on using the provisioned services

Requirements:

• Bachelor s degree in computer science, Engineering, or related field.
• Proven experience as a Cloud Engineer or similar role, with a focus on AI/ML solutions.
• Strong proficiency in provisioning and automating cloud infrastructure/platforms especially AI resources on the Azure platform.
• Experience with IAAS, PAAS, and SAAS enablement on the Azure platform.
• Experience with GenAI architecture principles, including RAG, LLM’s, and data pipelines.
• Solid understanding of data safety and security standards implementation.
• Familiarity with other cloud providers’ AI/ML offerings is an added advantage.
• Excellent communication skills and ability to collaborate effectively in a team environment.
• Analytical mindset with a strong attention to detail.
• Fast learner with a passion for staying updated on emerging technologies and industry trends.
• Good to have some python skills to provide samples to the teams on how to use the API s / security / services etc..