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We are seeking an AI Search Engineer to design, build, and operate production-grade search experiences powered by Azure AI Search. You will develop Python-based indexing and query services, implement vector/semantic and hybrid search patterns, and deploy secure, scalable workloads on Azure using Docker/Kubernetes. This role requires strong cloud engineering fundamentals, secure authentication/authorization practices, and disciplined deployment and operational excellence.
Job Responsibility:
Design and implement search solutions using Azure AI Search, including indexing strategies, schema design, and query patterns for relevance and performance
Build vector search and hybrid search capabilities (vector + keyword) to support semantic retrieval use cases
Implement ingestion and indexing pipelines (batch and/or streaming) to keep search indexes current and reliable
Develop backend services in Python (e.g., FastAPI/Flask) for search query orchestration, indexing automation, and integration with upstream/downstream systems
Implement robust error handling, retries, telemetry, and API contract documentation
Implement Microsoft Entra ID-based authentication and Azure RBAC for Azure AI Search access (preferred over key-based auth), including assignment of appropriate built-in roles for administration, indexing, and querying
Design access patterns for user- or application-scoped retrieval, including least-privilege access and secure token-based calls to the data plane
Containerize services using Docker and deploy/operate them on Kubernetes (e.g., AKS), including configuration, scaling, and environment promotion practices