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.