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Azure AI Architect

Job in Phoenix, Maricopa County, Arizona, 85003, USA
Listing for: JPC TECHNO INC
Full Time position
Listed on 2026-08-22
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Azure, AI Reliability/ Performance Engineer
Salary/Wage Range or Industry Benchmark: 140000 - 210000 USD Yearly USD 140000.00 210000.00 YEAR
Job Description & How to Apply Below

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 , 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
  • Lang Graph
  • Lang Smith
  • Lang Chain
  • 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
  • Lang Graph
  • Lang Chain
  • 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.

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