Azure AI/M365 Copilot Search - Architect
Cognizant
Job Description - Azure AI/M365 Copilot Search ArchitectKey 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).
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