GenAI Architect

Job description

**Skill** : GenAI Architect **Experience:** 8 -16 Years **Location:** Hyderabad, Bangalore, Pune, Mumbai, Noida, Chennai, Kolkata **NP** : Immediate to 30 Days **Job Description:** **Primary skills:** C#/.Net core with strong experience in Azure AI services and implementation. Worked on POCs/Proposals related to AI solutioning . **Secondary Skills** : Python **AI & Solution Engineering** - Design and implement AI-driven systems using: - Azure OpenAI, Azure AI Search, Azure ML - Azure AI Foundry (agent orchestration, lifecycle) - Microsoft Copilot Studio (enterprise copilots & workflows) - Build Retrieval-Augmented Generation (RAG) pipelines: - Chunking strategies (semantic, recursive, hybrid) - Embedding and vector search optimization - Develop multi-agent and conversational AI systems **Application Development (.NET Focus)** - Build and maintain scalable **.NET Core microservices** - Develop REST APIs integrating AI services into enterprise platforms - Ensure high performance, security, and resilience in distributed systems **Data & AI Pipeline Engineering** - Design intelligent data pipelines: - Data ingestion, transformation, embedding generation - Work with: - Vector databases (Azure AI Search, Cosmos DB) - SQL/NoSQL data stores - Ensure data quality, retrieval accuracy, and performance **AI Operations & Optimization** - Deploy and monitor AI systems in production - Optimize: - Token usage - Latency and throughput - Cost efficiency - Implement observability (logging, telemetry, feedback loops) - Manage model lifecycle (evaluation, retraining, tuning) **What You'll Bring** **Core Engineering Skills (Mandatory)** - Strong expertise in **.NET / C# (microservices architecture)** - Experience building and consuming **REST APIs** - Strong understanding of **cloud-native architecture (Azure)** **AI & Azure Expertise (Mandatory)** - Hands-on experience with: - Azure OpenAI (prompt engineering, optimization) - Azure AI Search (vector + hybrid search) - Azure ML (model lifecycle basics) - Practical implementation of: - RAG pipelines - Embedding strategies - Retrieval optimization **Copilot & Agentic AI** - Experience with **Copilot Studio** : - Conversational agents - Workflow automation - Exposure to **Azure AI Foundry** : - Agent orchestration - Multi-agent architecture (preferred for lead/architect) **Data & Database Skills (Critical Differentiator)** - Experience with: - Vector DB (Azure AI Search / Cosmos DB) - Relational DB (SQL Server) - NoSQL (Cosmos DB / MongoDB) - Understanding of: - Data pipelines / ETL - AI data preparation and indexing **Programming & AI Ecosystem** - Strong knowledge of **Python (AI/ML scripting)** - Experience with **Microsoft agent framework (preferred)** / **LangChain** - Familiarity with AI SDKs and APIs **DevOps & Quality** (Good to have) - Experience with **Azure DevOps (CI/CD)** - Understanding of: - Testing AI systems - Evaluation frameworks - Monitoring & telemetry