Azure AI M365 Copilot Search Architect

Job description

Job Title - Azure AI/M365 Copilot Search Architect Location- Pan India Experience - 6-12 Years Note - Notice Period - Immediate to 30 Days only. Please don't apply if you are not following under notice period criteria. Key Responsibilities • Design and implement enterprise GenAI search architectures leveraging Azure AI Search and Microsoft 365 Copilot search to deliver reliable, scalable, and intelligent discovery experiences across the organization. • Architect retrieval-augmented generation (RAG) patterns and semantic search solutions, selecting appropriate vector search, hybrid ranking, and grounding strategies for enterprise knowledge bases. • Analyze business requirements from diverse stakeholder groups and translate them into detailed search solution designs that balance relevance, latency, security, and cost. • Configure and optimize indexing pipelines for structured and unstructured data, ensuring consistent ingestion, enrichment, skillset application, and normalization across multiple content repositories. • Develop search relevance strategies including semantic ranking, vector embeddings, scoring profiles, synonym management, and domain-specific tuning to improve precision and recall for business-critical queries. Configure Microsoft 365 Copilot search connectors, semantic index integration, and Graph-based retrieval to surface organizational knowledge within Copilot experiences. • Collaborate with application engineering teams to integrate search and GenAI capabilities into web portals, internal tools, and customer-facing applications using appropriate SDKs and APIs. • Define and implement security and access models, ensuring search results respect data access policies, sensitivity labels, regulatory constraints, and privacy requirements. • Lead client-facing architecture and consulting engagements, presenting solution designs, conducting technical workshops, and advising stakeholders on GenAI search strategy and roadmap. • Monitor search system health by tracking relevance metrics, query latency, index freshness, and grounding quality, and recommend remediation to maintain high availability. • Conduct capacity planning and performance testing for search and GenAI workloads, predicting growth patterns and optimizing resource utilization across cloud environments. • Create detailed technical documentation for architectures, configurations, and runbooks, enabling operations teams to support and evolve search platforms efficiently. • Provide guidance on migration strategies from legacy search platforms to Azure AI Search and Copilot-based solutions, minimizing disruption and ensuring continuity of critical services. • Mentor junior engineers and architects on GenAI search technologies, design patterns, and best practices, fostering a culture of technical excellence and knowledge sharing. Required Skills • Hands-on expertise with Azure AI Search (index design, skillsets, semantic and vector search, scoring profiles). • Hands-on experience with Microsoft 365 Copilot search, Graph connectors, and semantic index integration. • Proven experience designing GenAI search solutions, including RAG architectures and embedding-based retrieval. • Strong background in search architecture and solution design for enterprise environments. • Demonstrated client-facing architecture and consulting engagement experience.