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AI Architect - Krish Services Group
AI Architect
Lead AI Architect to design and deploy production-grade AI systems, including RAG, LLM applications, and multi-agent workflows on Azure AI stack.
About the role
Key Responsibilities
- Design and deploy next-generation AI systems, including LLM applications, RAG systems, and multi-agent workflows, from concept to production.
- Develop reference architectures and canonical blueprints for RAG on Azure AI Search, agent runtimes on Azure AI Foundry, and LLM-backed assistants.
- Lead end-to-end AI system design, including model selection, retrieval design, orchestration, and deployment topology (AKS, Container Apps, APIM).
- Establish agent system frameworks, orchestration patterns, tool-use contracts, and evaluation harnesses using Azure AI Foundry Agent Service and Semantic Kernel.
- Build and maintain evaluation and observability layers with Azure Monitor, Application Insights, and tools like Braintrust or LangSmith.
- Drive R&D cadence, evaluate new Azure AI releases, and publish findings to upskill the AI engineering team.
Requirements
- 12+ years in software development, with 2–3 years shipping production AI/ML systems (LLM apps, RAG, or agent systems).
- Deep expertise in Azure AI stack (Foundry, AI Search, Azure OpenAI, AI Content Safety, AML) and hands-on production experience.
- Proficiency in Azure platform components (AKS, API Management, Cosmos DB, Fabric, Entra ID) and IaC (Bicep/Terraform).
- Familiarity with open-source orchestration tools (Semantic Kernel, LangGraph, AutoGen) and cross-cloud model APIs (Anthropic, OpenAI, Bedrock).
- Strong systems and data engineering skills, with a focus on latency, cost, and reliability tradeoffs.
Skills
azure ai foundryazure openairag systemsmulti agent workflowssemantic kernellanggraph