Azure AI/M365 Copilot Search - Architect

Job Description - Azure AI/M365 Copilot Search Architect

**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.

The Key Skills are Azure AI Search, Microsoft 365 Copilot Search

along with GenAI search solutions, Search Architecture , Solution Design, Client-facing architecture, and consulting engagements.

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关于高知特 (Cognizant)
高知特(Cognizant)（纳斯达克代码：CTSH）作为一家AI Builder和相关技术服务提供商，致力于通过打造全栈AI解决方案，帮助企业将人工智能投资转化为实际价值。公司凭借深厚的行业经验、流程优化和工程技术专长，将企业独特的业务场景融入科技系统，赋能组织释放人才潜能，推动切实成果，并帮助全球企业在瞬息万变的环境中保持领先。如需了解更多详情，敬请访问 cognizant.ai 或关注@cognizant。

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