Job time: GMT+8 time zone

The candidate should demonstrate a proven track record of delivering high-quality, scalable, and secure AI software solutions, including production platforms serving enterprise user bases.

Essential skills and experience include:

·         Deep expertise in RAG architecture design, vector search, hybrid retrieval, and enterprise search platforms utilizing Azure AI Search, Azure OpenAI, and custom embedding models.

·         Strong full-stack engineering proficiency in TypeScript, JavaScript, Python, Node.js/NestJS, and modern web frameworks (React).

·         Proven experience with cloud-native application development on Microsoft Azure, including Azure Container Apps, Service Bus, Key Vault, and Microsoft Foundry endpoints.

·         Extensive experience in Intelligent Document Processing (IDP), document layout parsing, structure-aware chunking, and text extraction (supported by published research in optical character recognition and text recognition).

·         Hands-on experience designing relational data models in Dataverse and integrating AI calls within Microsoft Power Platform environments (Power Apps, Power Automate).

·         Practical experience building automated evaluation harnesses, citation validators, structured output schema enforcement, and telemetry monitoring using Application Insights and Log Analytics.

Additional experience that would be advantageous:

·         Peer-reviewed research publications in computer vision, neural networks, or text recognition algorithms.

·         Prior experience serving as an AI Technical Lead or Data Science Lead guiding architectural decisions, model evaluation, and production optimization.

·         Demonstrated hands-on experience delivering AI solutions within Client’s tenant environment, holding an active client’s account and familiar with Power Platform and Azure AI integrations.

·         Experience with containerization tools (Docker), CI/CD build pipelines, and automated testing frameworks.

   Job time: GMT+8 time zone

The candidate should demonstrate a proven track record of delivering high-quality, scalable, and secure AI software solutions, including production platforms serving enterprise user bases.

Essential skills and experience include:

·         Deep expertise in RAG architecture design, vector search, hybrid retrieval, and enterprise search platforms utilizing Azure AI Search, Azure OpenAI, and custom embedding models.

·         Strong full-stack engineering proficiency in TypeScript, JavaScript, Python, Node.js/NestJS, and modern web frameworks (React).

·         Proven experience with cloud-native application development on Microsoft Azure, including Azure Container Apps, Service Bus, Key Vault, and Microsoft Foundry endpoints.

·         Extensive experience in Intelligent Document Processing (IDP), document layout parsing, structure-aware chunking, and text extraction (supported by published research in optical character recognition and text recognition).

·         Hands-on experience designing relational data models in Dataverse and integrating AI calls within Microsoft Power Platform environments (Power Apps, Power Automate).

·         Practical experience building automated evaluation harnesses, citation validators, structured output schema enforcement, and telemetry monitoring using Application Insights and Log Analytics.

Additional experience that would be advantageous:

·         Peer-reviewed research publications in computer vision, neural networks, or text recognition algorithms.

·         Prior experience serving as an AI Technical Lead or Data Science Lead guiding architectural decisions, model evaluation, and production optimization.

·         Demonstrated hands-on experience delivering AI solutions within Client’s tenant environment, holding an active client’s account and familiar with Power Platform and Azure AI integrations.

·         Experience with containerization tools (Docker), CI/CD build pipelines, and automated testing frameworks.