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Assistant Azure Ai Engineer Jobs (NOW HIRING)

ITR Group

Junior AI Engineer

Minneapolis, MN · On-site

Develop and support Generative AI applications using Azure AI services and OpenAI models. * Assist ... Collaborate with data engineers to prepare and optimize datasets for AI applications. * Evaluate AI ...

Programmers.io

Azure AI/ML Engineer

Bellevue, WA · On-site

$62 - $77/hr

AI,C#,ASP.NET 4.5,Java,LLM,Python,Vector,Semantic Kernel, AI Foundry ,LLMs (Azure OpenAI, OpenAI, Anthropic,MicroServices,Azure DevOps,Docker,Kubernetes Role Descriptions: 8 years of Strong ...

CBTS

Senior AI Developer (Azure AI)

Bay City, TX · On-site

$75/hr

Senior AI Developer (Azure AI) Location: Bay City, TX (Onsite, Mon Thurs, 4x10 Schedule) Employment: Contract / Contract-to-Hire Pay Rate: $75/hr on W2 We are seeking a Senior AI Developer to design ...

EffOne Technologies

Be Seen First

Azure AI Foundry Architect

Arlington, VA · Remote

$50 - $80/hr

This is a senior engineer/architect position that requires taking ownership of Cloud Architecture, Platform Engineering and DevOps. The ideal candidate will have expertise in Azure AI Foundry, GCP ...

GEI Consultants

AI Engineer

Cary, NC

$110K - $150K/yr

The AI Engineer is responsible for the development of AI solutions, typically leveraging pretrained ... Familiarity with Azure AI library APIs, including GPT, Codex, and DALL · E, and other frameworks ...

GEI Consultants

AI Engineer

Atlanta, GA

$110K - $150K/yr

The AI Engineer is responsible for the development of AI solutions, typically leveraging pretrained ... Familiarity with Azure AI library APIs, including GPT, Codex, and DALL · E, and other frameworks ...

GEI Consultants

AI Engineer

Pasadena, CA · On-site

The AI Engineer is responsible for the development of AI solutions, typically leveraging pretrained ... Familiarity with Azure AI library APIs, including GPT, Codex, and DALL • E, and other frameworks ...

GEI Consultants

AI Engineer

Manhattan, NY

$110K - $150K/yr

The AI Engineer is responsible for the development of AI solutions, typically leveraging pretrained ... Familiarity with Azure AI library APIs, including GPT, Codex, and DALL · E, and other frameworks ...

GEI Consultants

AI Engineer

Rancho Cordova, CA · On-site

The AI Engineer is responsible for the development of AI solutions, typically leveraging pretrained ... Familiarity with Azure AI library APIs, including GPT, Codex, and DALL • E, and other frameworks ...

GEI Consultants

AI Engineer

Dallas, TX

$110K - $150K/yr

The AI Engineer is responsible for the development of AI solutions, typically leveraging pretrained ... Familiarity with Azure AI library APIs, including GPT, Codex, and DALL · E, and other frameworks ...

GEI Consultants

AI Engineer

Wakefield, MA · On-site

$110K - $150K/yr

The AI Engineer is responsible for the development of AI solutions, typically leveraging pretrained ... Familiarity with Azure AI library APIs, including GPT, Codex, and DALL • E, and other frameworks ...

GEI Consultants

AI Engineer

Wakefield, MA

$110K - $150K/yr

The AI Engineer is responsible for the development of AI solutions, typically leveraging pretrained ... Familiarity with Azure AI library APIs, including GPT, Codex, and DALL · E, and other frameworks ...

GEI Consultants

AI Engineer

New York, NY · On-site

The AI Engineer is responsible for the development of AI solutions, typically leveraging pretrained ... Familiarity with Azure AI library APIs, including GPT, Codex, and DALL • E, and other frameworks ...

GEI Consultants

AI Engineer

Denver, CO

$110K - $150K/yr

The AI Engineer is responsible for the development of AI solutions, typically leveraging pretrained ... Familiarity with Azure AI library APIs, including GPT, Codex, and DALL · E, and other frameworks ...

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Assistant Azure Ai Engineer information

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$33K

$88.8K

$134.5K

How much do assistant azure ai engineer jobs pay per year?

As of Jul 11, 2026, the average yearly pay for assistant azure ai engineer in the United States is $88,754.00, according to ZipRecruiter salary data. Most workers in this role earn between $70,500.00 and $104,500.00 per year, depending on experience, location, and employer.

How much do Azure AI engineers make?

Azure AI engineers typically earn between $100,000 and $150,000 annually, depending on experience, location, and certifications. Senior roles or those with specialized skills in machine learning and cloud architecture can earn higher salaries. Compensation often includes benefits such as health insurance and professional development opportunities.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-paying position in artificial intelligence, such as an senior Azure AI Engineer or AI research lead, often requiring advanced skills in machine learning, cloud platforms like Azure, and extensive experience. Such roles may involve overseeing AI projects, developing innovative solutions, and managing teams, with compensation reflecting expertise and responsibility.

Which 3 jobs will survive AI?

For an Assistant Azure AI Engineer, roles that require complex problem-solving, creativity, and human interaction are more likely to survive AI automation. These include jobs like AI specialists who develop and fine-tune models, cybersecurity analysts protecting AI systems, and data scientists interpreting AI outputs. Skills in critical thinking, domain expertise, and continuous learning will remain valuable in AI-driven environments.

What does an Assistant Azure AI Engineer do?

An Assistant Azure AI Engineer supports the design, development, and deployment of artificial intelligence solutions using Microsoft Azure's cloud platform. They assist more senior engineers in building, testing, and maintaining AI models and services, such as natural language processing, computer vision, and machine learning. Common tasks include preparing data, configuring Azure AI services, integrating models into applications, and monitoring their performance. This role often involves collaboration with data scientists, developers, and IT teams to ensure AI solutions meet business needs and operate efficiently.

What types of projects and collaboration can an Assistant Azure AI Engineer expect in their first year?

As an Assistant Azure AI Engineer, you’ll typically start by working on smaller components of larger AI projects, such as developing, testing, or deploying machine learning models using Azure’s tools. You’ll frequently collaborate with data scientists, software developers, and cloud architects to integrate AI solutions into existing systems. Expect to participate in team meetings, code reviews, and brainstorming sessions to solve real-world business challenges. Over time, you may take on more complex tasks and gain exposure to end-to-end project workflows, setting a solid foundation for career growth.

What are the key skills and qualifications needed to thrive as an Assistant Azure AI Engineer, and why are they important?

To thrive as an Assistant Azure AI Engineer, you need a solid background in computer science, proficiency in programming languages like Python, and a foundational understanding of machine learning concepts, often supported by a relevant degree or certification. Familiarity with Microsoft Azure AI tools, such as Azure Machine Learning, Cognitive Services, and DevOps pipelines, is typically required. Strong problem-solving abilities, effective communication, and a willingness to learn new technologies help candidates excel in this evolving field. These skills and qualities are crucial for building scalable AI solutions and collaborating effectively within diverse technical teams.

What engineer makes $500,000 a year?

Senior AI engineers, including those working with cloud platforms like Azure and specializing in AI and machine learning, can earn salaries approaching or exceeding $500,000 annually, especially with extensive experience, advanced skills, and in high-demand industries. Compensation often includes bonuses, stock options, and other benefits, reflecting the value of expertise in AI development and deployment at scale.

What is the difference between Assistant Azure Ai Engineer vs Data Scientist?

AspectAssistant Azure Ai EngineerData Scientist
Required CredentialsAzure certifications, basic programming skillsStatistics, data analysis, programming (Python/R)
Work EnvironmentCloud platforms, AI development teamsData analysis, research, modeling
Industry UsageAI solutions, cloud servicesData analysis, predictive modeling

The Assistant Azure Ai Engineer primarily focuses on developing and deploying AI solutions within Azure cloud environments, often working with AI tools and services. In contrast, Data Scientists analyze data, build models, and generate insights, often using statistical and programming skills. While both roles involve data and AI, the Assistant Azure Ai Engineer emphasizes cloud-based AI deployment, whereas Data Scientists focus on data analysis and modeling.

What cities are hiring for Assistant Azure Ai Engineer jobs? Cities with the most Assistant Azure Ai Engineer job openings:
What are the most commonly searched types of Azure Ai Engineer jobs? The most popular types of Azure Ai Engineer jobs are:
What states have the most Assistant Azure Ai Engineer jobs? States with the most job openings for Assistant Azure Ai Engineer jobs include:
Assistant Azure Ai Engineer jobs near you
AI Engineer -- Immediate Interview

AI Engineer -- Immediate Interview

MethodHub

Fort Worth, TX • On-site

Other

Posted 22 days ago

Job description

Job Title: Sr AI Engineer 
Experience Level: 7-10 years
Location: Fort Worth, TX (Hybrid)
Client: Direct
 
Job Summary 
We are seeking a skilled AI Engineer to build, integrate, and operationalize AI/ML models and agent workflows on AWS and Azure as the core AI foundation, with Microsoft Copilot as the primary user experience layer. The role involves collaborating with AI Architects and data teams to deploy scalable, production-grade AI solutions that are grounded in enterprise data, governed responsibly, and optimized for real-world performance. The candidate should be able to own the full AI engineering lifecycle, from prototyping and integration through to production deployment and ongoing optimization. 

Key Responsibilities 

LLM & Agent Development 
• Build, integrate, and iterate on LLM-powered agent experiences for enterprise knowledge access and workflow automation. 
• Own prompt engineering, orchestration logic, and multi-agent workflow design using AWS Bedrock and Azure AI services. 
• Implement grounding, citation enforcement, and refusal behavior patterns aligned with enterprise governance standards. 
• Build structured triage and escalation logic within agent workflows to support robust, production-grade AI systems. 
• Own the AI engineering layer end to end, from prototype through pilot validation and production deployment. 

RAG & Retrieval Engineering 
• Implement RAG pipelines using structured and unstructured enterprise data on AWS and Azure cloud-native services. 
• Tune retrieval quality through vector search, re-ranking strategies, and context window optimization. 
• Work with embedding models, chunking strategies, and hybrid retrieval approaches to improve answer relevance. 
• Integrate vector databases such as Azure AI Search and Amazon OpenSearch to support enterprise RAG systems. 

Required Qualifications 
• 6-10 years of overall experience with 3+ years building LLM-powered applications in production or near-production environments. 
• Hands-on experience with AWS AI/ML services (Bedrock, SageMaker) and Azure AI services (Azure AI Foundry, Azure OpenAI Service, Azure ML). 
• Experience integrating with Microsoft Copilot or building Copilot extensibility solutions (plugins, connectors, or agents). 
• Hands-on experience with RAG architectures: vector search, embedding models, chunking strategies, and hybrid retrieval. 
• Strong understanding of grounding techniques, hallucination mitigation, and AI evaluation methodologies. 
• Experience with agent orchestration frameworks and patterns: multi-agent routing, workflow chaining, and context management. 
• Strong Python skills; familiarity with LangChain, Semantic Kernel, or equivalent agent orchestration frameworks preferred. 
• Ability to work autonomously and own the full AI engineering stack within a cross-functional delivery team. 

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