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Generative Ai Engineer Intern Jobs in Arizona (NOW HIRING)

Stantec

Generative AI Developer

Phoenix, AZ · On-site

Stantec is a company dedicated to creating a caring culture where everyone can thrive, seeking a Generative AI Developer to enhance their Digital Center of Excellence. This role involves designing ...

Stantec

Generative AI Developer

Phoenix, AZ · On-site

$104K - $152K/yr

Your Opportunity We are seeking a GenAI Developer to drive the design, maturation, and enterprise deployment of generative AI and agentic AI systems within Stantec's Digital Center of Excellence ...

Rubin Obs

Principal AI Engineer

Tucson, AZ · On-site

$179 - $226/hr

Assess and implement emerging technologies, including generative AI, foundation models, LLMs, AI ... Mentor engineers, scientists, and technical teams in AI technologies, architecture, and responsible ...

New

Teaching with Telescopes

Principal AI Engineer

Tucson, AZ · On-site

$179 - $226/hr

Assess and implement emerging technologies, including generative AI, foundation models, LLMs, AI ... Mentor engineers, scientists, and technical teams in AI technologies, architecture, and responsible ...

New

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Generative Ai Engineer Intern information

What does a generative AI engineer intern do?

A Generative AI Engineer Intern assists in developing and testing machine learning models, specifically those that can create new content such as text, images, or audio. They work with frameworks like TensorFlow or PyTorch, collaborate with senior engineers, and help improve the performance and reliability of generative AI systems. Interns may also be involved in data preprocessing, model evaluation, and keeping up with the latest research in artificial intelligence.

What skills and qualifications are needed to thrive as a generative AI engineer intern?

To thrive as a Generative AI Engineer Intern, you need a solid understanding of machine learning fundamentals, programming skills (especially in Python), and coursework or experience in artificial intelligence or computer science. Familiarity with deep learning frameworks like TensorFlow or PyTorch and version control systems such as Git is typically required, and relevant coursework or certifications in AI/ML are advantageous. Strong problem-solving skills, curiosity, and the ability to communicate complex ideas clearly help interns stand out. These skills and qualities are crucial for quickly learning advanced AI techniques, contributing to team projects, and driving innovation in a rapidly evolving field.

What types of projects can a generative AI engineer intern expect to work on during their internship?

As a Generative AI Engineer Intern, you can expect to work on projects involving the development, training, and evaluation of generative models such as GANs, VAEs, or transformer-based architectures. Typical tasks may include data preprocessing, model implementation, fine-tuning, and running experiments to improve model performance. Interns often collaborate closely with data scientists, software engineers, and research teams, gaining exposure to both research and application of AI in real-world products. This role provides hands-on experience with state-of-the-art tools and frameworks, offering a valuable foundation for a future career in AI engineering or research.

What is the difference between Generative Ai Engineer Intern vs Machine Learning Engineer Intern?

AspectGenerative Ai Engineer InternMachine Learning Engineer Intern
Required CredentialsBasic knowledge of AI, programming, and some coursework in machine learning or AIStrong foundation in machine learning, programming, and data analysis, often with coursework or certifications
Work EnvironmentTech companies, startups, research labs focusing on AI applicationsTech firms, research institutions, and companies applying machine learning models
Industry UsageDeveloping generative models like GPT, DALL·E, and similar AI toolsBuilding predictive models, data pipelines, and machine learning algorithms

While both roles involve AI and machine learning, a Generative Ai Engineer Intern focuses specifically on creating generative models like text, images, or audio, whereas a Machine Learning Engineer Intern works broadly on developing and deploying various machine learning algorithms across different applications.

What are the most commonly searched types of Generative Ai Engineer jobs in Arizona? The most popular types of Generative Ai Engineer jobs in Arizona are:
What are popular job titles related to Generative Ai Engineer Intern jobs in Arizona? For Generative Ai Engineer Intern jobs in Arizona, the most frequently searched job titles are:
What job categories do people searching Generative Ai Engineer Intern jobs in Arizona look for? The top searched job categories for Generative Ai Engineer Intern jobs in Arizona are:
What cities in Arizona are hiring for Generative Ai Engineer Intern jobs? Cities in Arizona with the most Generative Ai Engineer Intern job openings:
Generative Ai Engineer Intern jobs near you
Infographic showing various Generative Ai Engineer Intern job openings in Arizona as of August 2026, with employment types broken down into 17% Internship, 66% Full Time, and 17% Part Time. Highlights an 100% In-person job distribution.

Generative AI Developer

Stantec

Phoenix, AZ • On-site

Full-time

Re-posted 4 days ago

Stantec rating

8.5

Company rating: 8.5 out of 10

Based on 83 frontline employees who took The Breakroom Quiz

112th of 441 rated engineering

Job description

Job Summary:
Stantec is a company dedicated to creating a caring culture where everyone can thrive, seeking a Generative AI Developer to enhance their Digital Center of Excellence. This role involves designing and deploying generative AI solutions, collaborating with various teams to ensure the solutions are scalable, secure, and compliant with governance principles.
Responsibilities:
• Design, build, and deploy end-to-end GenAI solutions and agentic solutions, including model lifecycle management, evaluation, deployment, and monitoring.
• Partner with ML/AI leads and engineering teams to integrate LLMs, autonomous agents, and GenAI services into existing and new solution pipelines.
• Review and advise on infrastructure approaches, including containerization, orchestration, and infrastructure-as-code to ensure scalability, security, and operational readiness.
• Collaborate with product owners, engineering, security, and data teams to design solutions that meet functional and non-functional requirements (performance, reliability, compliance, and cost).
• Establish and enforce governance for model usage, prompt and tool management, safety controls, data handling, and lifecycle management.
• Design integrations with enterprise data platforms, knowledge sources, and APIs, ensuring appropriate access controls and auditability.
• Document architectural patterns, methodologies, and lessons learned.
• Evaluate emerging GenAI technologies and recommend adoption strategies based on business value and risk.
• Stay current with emerging research, tools, and frameworks in Generative AI, Agentic AI, and multi-agent systems.
• Design, build, and deploy agentic solutions using Microsoft Copilot Studio, including configuration of topics, actions, integrations, and orchestration logic.
Qualifications:
Required:
• Strong background in designing and delivering modern cloud solutions, APIs, and data/AI platforms.
• Demonstrated knowledge and hands-on experience in building custom AI agents, including development using platforms such as Azure AI Foundry and Microsoft Copilot Studio.
• Familiarity with security, privacy, and governance practices for enterprise AI solutions.
• Ability to communicate complex concepts clearly to technical and non-technical audiences, influencing stakeholders through architecture guidance.
• Experience partnering across disciplines in agile delivery environments.
• Understanding application deployment, hosting, and scaling within Azure.
• Master’s degree or higher degree in Computer Science, Engineering, or related field (or equivalent experience).
• 5+ years of professional experience in AI/ML solution delivery, with recent hands-on GenAI solution experience.
• Experience deploying AI/GenAI solutions in Azure environments, including familiarity with Azure AI Foundry.
Preferred:
• Experience developing AI agents in Microsoft Copilot Studio is highly preferred.
Company:
Stantec is a professional services company that provides engineering, architecture, design, and consulting services. Founded in 1954, the company is headquartered in Edmonton, CAN, with a team of 10001+ employees. The company is currently Late Stage.

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