Civil, Structural & Architectural Responsible Engineer leading CS&A design on critical nuclear infrastructure projects. Overseeing project delivery ensuring compliance and budget meet expectations.
About the role
- Senior Lead Architect creating AI solutions on Azure with focus on GenAI-first design. Leading architecture reviews and evaluating new Azure GenAI capabilities.
Responsibilities
- Architect end-to-end GenAI-first and Agentic AI solutions on Azure using: Azure OpenAI Service, Azure AI Foundry, Azure Agents (Agent Service + Agent Runtime), Microsoft Agent Framework SDK, Azure Machine Learning (Azure ML) for model lifecycle, fine-tuning & evaluation
- Design multi-agent systems capable of planning, reasoning, memory management, tool invocation, and complex workflow execution
- Architect enterprise-grade RAG systems using: Azure Cognitive Search, Azure AI Search, Vector Stores, Cosmos DB + pgvector, Redis Enterprise on Azure
- Build secure prompt pipelines, embeddings workflows, tool integration layers, and model evaluation frameworks optimized for Azure’s GenAI stack
- Build Python-based microservices (FastAPI/Django) tightly integrated with Azure AI and cloud-native components
- Implement enterprise-grade LLMOps using: Azure ML Pipelines, Azure DevOps (ADO), GitHub Actions for MLOps/LLMOps, Azure Monitor, App Insights, Log Analytics for observability
- Establish engineering standards for: Agent governance & safety, Content filters & guardrails (Azure OpenAI Safety Systems), Secure model invocation via private endpoints, Latency reduction, performance tuning & cost governance
- Optimize AI workloads using model caching, selective batching, adaptive routing, vector index optimization, and autoscaling strategies on AKS/Functions
- Lead architecture reviews, threat modeling, cost modeling, and performance benchmarking for large-scale GenAI workloads
- Evaluate new Azure GenAI capabilities, FMs, agent frameworks, vector databases, and orchestration tools
- Build internal accelerators and reusable reference architectures for: Multi-agent orchestration with Azure Agents Framework, Langgraph, CrewAI RAG 2.0 and context enrichment pipelines, Federated & hybrid retrieval patterns, Enterprise system/tool integration
- Drive PoCs, prototypes, and tech spikes to validate emerging Azure GenAI capabilities and accelerate enterprise adoption
Requirements
- Microsoft Certified Azure Solutions Architect Expert or equivalent Azure Architect certification
- Strong hands-on experience designing AI/ML or GenAI systems on Azure
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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