Azure AI Architect

Python, REST APIs

We are seeking a highly skilled Azure AI / Agentic AI Architect to design, build, and scale enterprise-grade AI platforms using Azure AI Services.

The role focuses on multi-agent architectures, Generative AI, and intelligent automation, enabling business transformation through scalable, secure, and governed AI solutions.

Responsibilities

• Design and implement Azure-based Agentic AI solutions leveraging Azure OpenAI, Azure AI Services, and multi-agent orchestration frameworks for enterprise use cases.
• Architect enterprise AI platforms using Azure AI Foundry, Agent Services, APIs, and modern data pipelines to enable scalable and reusable AI capabilities.
• Develop and orchestrate multi-agent workflows including reasoning, tool/function calling, memory management, and agent-to-agent communication.
• Integrate Generative AI, NLP, and ML models into enterprise applications using Azure OpenAI, Cognitive Services, and RAG-based architectures with Azure AI Search.
• Build AI-powered solutions such as copilots, virtual assistants, intelligent automation workflows, recommendation systems, and analytics platforms.
• Design end-to-end AI architecture layers including interaction, orchestration, integration, model enablement, and data layers aligned with enterprise standards.
• Evaluate and implement AI/ML models and tools based on performance, scalability, cost optimization, and use-case suitability.
• Ensure Responsible AI, governance, and security compliance using Azure capabilities such as Entra ID, Key Vault, Content Safety, and enterprise guardrails.
• Implement observability and LLMOps practices including monitoring, evaluation, drift detection, performance tuning, and telemetry using Azure Monitor and Application Insights.
• Collaborate with cross-functional stakeholders (product, engineering, business teams) to convert business requirements into scalable AI solutions.
• Develop architecture diagrams, technical documentation, and deployment strategies for enterprise AI platforms.
• Lead PoCs and innovation initiatives to validate AI use cases and accelerate production adoption.

Must-Have Skills

• Hands-on experience with Azure AI Services
• Cognitive Services
• Strong experience in:
• GenAI / LLMs
• RAG
• Prompt Engineering
• Agentic AI frameworks
• Multi-agent orchestration
• LangGraph
• LangSmith
• LangChain
• Semantic Kernel
• Experience in:
• Python
• Modern AI/ML frameworks
• Knowledge of:Embeddings
• Semantic Search
• Experience with cloud-native architectures (Azure preferred)
• Strong understanding of:
• APIs
• Microservices

Good-to-Have Skills

• Experience with:
• Agent Services
• Knowledge of:
• CI/CD
• Evaluation frameworks
• Experience with:
• Exposure to:
• Responsible AI
• AI governance frameworks

Summary of the Role

Core Technologies:

• Agent Services
• LangGraph
• LangChain
• Semantic Kernel
• Python
• RAG
• LLMOps
• Databricks

Primary Focus: Building enterprise-grade multi-agent AI systems, copilots, RAG applications, AI automation platforms, and governed GenAI solutions on Azure.