AI/ML Platform Engineer

About Company

Papigen is a fast-growing global technology services company, delivering innovative digital solutions through deep industry experience and cutting-edge expertise. We specialize in technology transformation, enterprise modernization, and dynamic areas like Cloud, Big Data, Java, React, DevOps, and more. Our client-centric approach combines consulting, engineering, and data science to help businesses evolve and scale efficiently.

About The Role

Scope of WorkAbout the Role:

We’re seeking to engage an AI/ML Platform Engineer who can support the design, development, and secure deployment of AI/ML applications on cloud platforms.

This role bridges the gap between application development teams and cloud platform teams, ensuring solutions are scalable, secure, and compliant with World Bank policies.

Scope of Work

Architecture & Security (50%)

• Collaborate with stakeholders to gather requirements for AI/ML applications.
• Design scalable, secure, and cost-effective cloud architectures.
• Develop architecture diagrams and security documentation.
• Conduct security assessments to ensure compliance with best practices and World Bank policies.
  
  

Platform Engineering (50%)

• Act as the primary liaison between app teams and platform teams.
• Drive smooth integration, deployment, and operations of AI/ML solutions.
• Provide technical guidance, training, and support for cloud-based AI/ML platforms.
• Contribute to process improvements and knowledge sharing.
  
  

Skills & Experience

• Proven experience as a Cloud Solution Architect / Platform Engineer with focus on AI/ML applications.
• Strong hands-on knowledge of Azure and Google Cloud.
• Experience with AI/ML frameworks: TensorFlow, PyTorch, LangChain, LangGraph.
• Excellent communication and documentation skills.
• Relevant certifications are a plus (e.g., Azure Solutions Architect Expert, Google Cloud Architect).
  
  

Skills: ml,cloud,azure,microsoft azure,artificial intelligence,machine learning,terraform,docker,kubernetes,azure data factory,spark,mlops