Senior Search and AI Engineer

Are you passionate about AI-powered search and document intelligence? Do you thrive on designing and deploying cutting-edge retrieval systems that leverage RAG, vector search, and AI-driven document processing? We are seeking a Senior AI Engineer to lead the development of intelligent search and retrieval solutions. In this role, you will work with Azure AI Search, Retrieval-Augmented Generation (RAG), Query Orchestration, and Kubernetes-based deployments to build scalable, high-performance AI-driven search systems. �� Key Responsibilities
• Architect & Deploy AI-powered search and document intelligence solutions using Azure AI Search, Azure Document Intelligence, and RAG
• Optimize Query Orchestration to intelligently route queries across multiple search and retrieval systems
• Develop & Fine-Tune RAG-based AI applications to enhance knowledge retrieval from structured and unstructured documents
• Deploy & Manage containerized AI applications using Azure Kubernetes Service (AKS) for scalable search solutions
• Enhance Vector Search Pipelines with embeddings and hybrid search techniques to improve document retrieval accuracy
• Implement On-Premise AI Solutions using open-source tools like Tesseract OCR, PyMuPDF, and Pillow
• Integrate with APIs (Profile APIs, Product Metadata APIs, Download APIs) to enrich indexing and search functionalities
• Ensure Compliance with export control regulations and best practices for secure document handling
• Monitor & Optimize AI Workflows for efficient document processing, retrieval, and search performance
• Collaborate with stakeholders to refine AI-powered solutions based on business needs

�� Required Qualifications ✅ 5+ years of experience in AI/ML, search, and document processing✅ Expertise in Query Orchestration for AI-driven search and retrieval pipelines✅ Strong knowledge of Retrieval-Augmented Generation (RAG) architectures✅ Hands-on experience with Azure AI Search, Document Intelligence, and Cognitive Services✅ Proficiency in vector search techniques, embeddings, and hybrid search architectures✅ Strong experience with Kubernetes (AKS) & containerized AI deployments✅ Hands-on experience with on-premise document processing tools like Tesseract OCR, PyMuPDF, and Pillow✅ Proficiency in Python for developing AI search pipelines✅ Bonus: Experience with Azure OpenAI, LangChain, or AI Foundry �� Preferred Qualifications
• Hybrid Cloud AI Expertise - Experience in on-prem + cloud AI solutions
• Deep Query Orchestration Knowledge - Optimizing multi-index search workflows
• Vector Database Experience - Proficiency in FAISS, Weaviate, or Pinecone
• NLP & Document Classification - Strong background in entity extraction and natural language processing
• Security & Compliance - Familiarity with export control restrictions and secure document handling best practices