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Azure AI Engineer
StratEdge It consulting INCBellevue, WA🇺🇸United StatesPosted 29 Jul 2026
Quick Overview
Salary
$70k - $98k/yr
Work Type
On Site
Level
Mid Senior
Job Description
Title: Azure AI Engineer
Location: Bellevue, WA/Onsite
Duration: Full Time
Client: Confidential
Salary Range: $70k-$98K/year
Visa: GC
Experience required: 5- 8 years of experience
Interview Mode: Video
Job Description
Must Have Technical/Functional Skills:
Agentic AI Frameworks & Autonomous Workflow Design; LLM Orchestration; Prompt Engineering & AI Agents; Azure Cloud-Native Development & Microservices; Python; C#; Embeddings & AI Evaluation Frameworks; AI/ML Systems Development & Production Deployment. Sentiment Analysis & NLP Solutions; Azure AI Foundry; Azure OpenAI.
Roles & Responsibilities:
Architect, design, and implement large-scale agentic AI solutions for sentiment intelligence.
Build and optimize cloud-scale Azure services for reliability, performance, and scalability.
Develop LLM orchestration frameworks, prompt pipelines, and agent workflows.
Collaborate with product, research, applied science, and data engineering teams to deliver AI-powered capabilities.
Drive AI technical strategy, engineering excellence, experimentation, and innovation.
Ensure security, compliance, operational excellence, and responsible AI adoption.
Location: Bellevue, WA/Onsite
Duration: Full Time
Client: Confidential
Salary Range: $70k-$98K/year
Visa: GC
Experience required: 5- 8 years of experience
Interview Mode: Video
Job Description
Must Have Technical/Functional Skills:
Agentic AI Frameworks & Autonomous Workflow Design; LLM Orchestration; Prompt Engineering & AI Agents; Azure Cloud-Native Development & Microservices; Python; C#; Embeddings & AI Evaluation Frameworks; AI/ML Systems Development & Production Deployment. Sentiment Analysis & NLP Solutions; Azure AI Foundry; Azure OpenAI.
Roles & Responsibilities:
Architect, design, and implement large-scale agentic AI solutions for sentiment intelligence.
Build and optimize cloud-scale Azure services for reliability, performance, and scalability.
Develop LLM orchestration frameworks, prompt pipelines, and agent workflows.
Collaborate with product, research, applied science, and data engineering teams to deliver AI-powered capabilities.
Drive AI technical strategy, engineering excellence, experimentation, and innovation.
Ensure security, compliance, operational excellence, and responsible AI adoption.
Skills
Microservices
NLP
Azure
C#
LLM
Python
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