Gen AI Architect

Gen AI ArchitectWe are seeking a highly experienced Principal Solution Architect – Agentic AI & GenAI to lead the design and deployment of enterprise-scale, agent-driven AI systems. This role will drive innovation across multi-agent architectures, LLM orchestration platforms, and Retrieval-Augmented Generation (RAG) on Microsoft Azure, with measurable business impact across enterprise domains.The ideal candidate combines deep technical expertise in agentic frameworks with architectural vision and has successfully delivered production-grade autonomous AI systems at scale.Key Responsibilities1. Agentic AI Architecture Leadership (Core)Define and own the architecture for multi-agent systems — including planner/executor patterns, tool-use orchestration, agent-to-agent communication, and human-in-the-loop workflowsLead design and deployment using agentic frameworks such as LangGraph, LangChain, AutoGen, CrewAI, Semantic Kernel, and Azure AI Agent ServiceArchitect agent memory, state management, and long-running workflow patterns (short-term, long-term, episodic memory)Design agent evaluation, guardrails, and safety frameworks for autonomous decision-makingEstablish patterns for tool/function calling, MCP (Model Context Protocol) servers, and enterprise system integration from agents2. Azure-First GenAI Platform ArchitectureOwn end-to-end architecture on Microsoft Azure, leveraging:Azure OpenAI Service, Azure AI Foundry, Azure AI Agent ServiceAzure AI Search (vector + hybrid retrieval), Cosmos DB, Azure SQLAzure Kubernetes Service (AKS), Azure Functions, Container AppsAzure API Management, Event Grid, Service BusAzure Monitor, Application Insights for AI observabilityDesign secure, scalable, and cost-efficient AI solutions aligned with Azure Well-Architected FrameworkLead architecture decisions across model selection, fine-tuning, evaluation, and deployment within the Azure ecosystem3. RAG & Knowledge SystemsArchitect and implement enterprise RAG frameworks using Azure AI Search and vector databasesDesign ingestion pipelines for structured and unstructured data (PDFs, documents, enterprise data)Optimize retrieval strategies — hybrid search, semantic re-ranking, query rewriting, and chunking strategiesIntegrate RAG as a tool/capability within agentic workflows4. Platform & Engineering ExcellenceBuild reusable AI platforms and frameworks to accelerate solution delivery across teamsDrive adoption of microservices, event-driven architectures (Kafka / Azure Event Hubs), and API-first designEnsure robustness through monitoring, evaluation frameworks, tracing (LangSmith, Langfuse, Azure AI evaluations), and feedback loops5. Model Strategy & OptimizationEvaluate and deploy LLMs across Azure OpenAI (GPT family), open-source models (Llama, Mistral), and fine-tuned variantsImplement prompt engineering, guardrails, and hallucination mitigation strategiesOptimize for latency, cost, token efficiency, and performance in production agent workflows6. Governance & Responsible AIEstablish best practices for AI safety, explainability, and compliance for autonomous agentsImplement data governance, privacy, and security standards (Azure Purview, Microsoft Defender for Cloud)Define human-oversight patterns for high-stakes agentic decisions7. Leadership & MentorshipMentor senior engineers and architects in agentic AI and GenAI best practicesDrive technical direction across multiple teams and projectsInfluence leadership on AI strategy and roadmapRequired Qualifications12+ years of experience in software engineering / AI / ML3+ years in architect or technical leadership rolesProven hands-on experience building and deploying agentic AI systems (multi-agent orchestration, tool-use, autonomous workflows) in productionStrong expertise with:Agentic frameworks: LangGraph, LangChain, AutoGen, CrewAI, Semantic Kernel, or equivalentGenerative AI & LLMs — prompt engineering, function calling, fine-tuningRAG architectures and vector databases (Azure AI Search, Pinecone, Weaviate, etc.)Microsoft Azure — Azure OpenAI, Azure AI Foundry, AKS, and the broader Azure data/AI ecosystemDistributed systems and scalable backend architecture expertiseProven experience delivering production AI systems at enterprise scaleStrong programming skills in Python; experience with ML frameworks and API designExperience with real-time/event-driven systems (Kafka, Azure Event Hubs, streaming pipelines)Key SkillsAgentic AI & Multi-Agent SystemsGenerative AI (LLMs, prompt engineering, fine-tuning)Retrieval-Augmented Generation (RAG)Microsoft Azure AI & Data PlatformSystem Design & Distributed ArchitectureData Engineering & PipelinesAI Evaluation, Observability & GuardrailsStakeholder Management & Technical Leadership

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