Azure Agentic AI only USC and GC w2

Envision Technology Solutions; United States; On-site; USD 140,000 - 210,000; Full time

Job summary

Envision Technology Solutions is seeking an Azure Agentic AI expert skilled in LangGraph/LangChain, MCP integrations, and enterprise governance. You will design and implement multi-agent workflows on Azure, with emphasis on RAG, evaluation, observability, and secure, scalable AI deployments.

The role requires strong Python and REST API development, experience with Docker/AKS, and building CI/CD pipelines. You will contribute to defining AI governance and lifecycle management across enterprise

Qualifications

• Experience with Azure AI / GenAI platforms and enterprise deployments.
• Implement MCP integrations between AI agents and enterprise apps.
• Design multi-agent workflows and agent orchestration.
• Develop RAG and knowledge retrieval solutions on Azure.
• Establish AI evaluation frameworks using DeepEval, RAGAS and Azure capabilities.
• Implement observability with OpenTelemetry in AI workloads.
• Secure identity and access with Azure IAM, OAuth, and OBO.
• Containerize workloads with Docker and AKS.
• Build pipelines with Terraform and GitHub/GitLab CI/CD.
• Governance, guardrails and agent lifecycle management.

Responsibilities

• Design and develop Agentic AI and multi-agent solutions using Azure GenAI.
• Build agent workflows using LangGraph, LangChain and Strands.
• Implement MCP integrations connecting agents with apps and data sources.
• Design RAG and knowledge retrieval solutions on Azure.
• Establish AI evaluation frameworks using DeepEval, RAGAS and Azure capabilities.
• Implement AgentOps, tracing and observability with OpenTelemetry.
• Develop scalable integrations with Azure Functions, API Management, REST APIs and event-driven architecture.
• Implement secure identity and access patterns using Azure IAM, OAuth, and OBO.
• Deploy containerised AI workloads using Docker, Azure Container Registry and AKS.
• Build automated infrastructure and delivery pipelines using Terraform and GitHub/GitLab CI/CD.
• Establish AI governance and agent lifecycle management for enterprise deployments.

Skills

Azure AI / GenAI

LangGraph

LangChain

Strands

Agentic AI

MCP integrations

RAG / knowledge solutions

Python

REST APIs

AI evaluation

OpenTelemetry observability

Azure Functions

Azure API Management

Azure IAM / OAuth / OBO

Docker / ACR / AKS

Microservices / event-driven

AI governance & guardrails

Agent lifecycle management

Job description

We are looking for a Azure Agentic AI expert skilled in LangGraph/ LangChain, MCP, multi-agent workflows, RAG, Python, AI evaluation, observability, and enterprise AI governance.

Key Responsibilities

• Design and develop Agentic AI and multi-agent solutions using Azure AI and Azure-native GenAI services.
• Build agent workflows and orchestration using LangGraph, LangChain and/or Strands.
• Implement MCP (Model Context Protocol) integrations connecting AI agents with enterprise applications, APIs and data sources.
• Design and implement enterprise RAG and knowledge retrieval solutions on Azure.
• Establish AI evaluation frameworks using DeepEval, RAGAS and Azure-native evaluation capabilities.
• Implement AgentOps, tracing, monitoring and observability using OpenTelemetry and Azure-native services.
• Develop scalable integrations using Azure Functions, API Management, REST APIs and event-driven architectures.
• Implement secure identity and access patterns using Azure IAM, OAuth and OBO.
• Deploy containerised AI workloads using Docker, Azure Container Registry and AKS.
• Build automated infrastructure and delivery pipelines using Terraform/Azure-native IaC and GitHub/GitLab CI/CD.
• Establish AI governance, guardrails and agent lifecycle management for enterprise deployments.

Required Skills

• Strong hands-on experience with Azure AI / Azure-native GenAI platforms
• Agent frameworks: LangGraph, LangChain, Strands
• Agentic AI and multi-agent workflow orchestration
• MCP integrations
• RAG and enterprise knowledge solutions
• Python and REST APIs
• DeepEval, RAGAS and AI evaluation
• OpenTelemetry and AI/Agent observability
• Azure Functions and Azure API Management
• Azure identity, OAuth/OBO and security
• Docker, ACR and AKS
• Microservices and event-driven architecture
• AI governance, guardrails and agent lifecycle management

Preferred

• Experience delivering secure, scalable enterprise Agentic AI solutions into production.