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Genai Engineer Jobs in Arizona (NOW HIRING)

GenAI Engineer - SRE

Phoenix, AZ · On-site

$56.50 - $75.25/hr

GenAI Engineer Location: Phoenix, AZ (Client Site - No Remote, No Virtual) Work Model: Hybrid (4 days onsite Mon-Thu, Friday remote) Interviews: 2-3 rounds (including client interview) Role Summary ...

Lead GenAI Engineer (LLM)

Tempe, AZ · Hybrid

$98K - $129K/yr

Design & Deploy AI/GenAI Solutions -- Architect and implement LLM-powered applications, agentic ... Engineer Data & Analytics Pipelines -- Build pipelines that feed AI/ML systems with clean, governed ...

... Engineer to support their Information Security applications within the organization. This job will have the following responsibilities: * You will utilize your strong AI capabilities and GenAI ...

Customer Enablement & Training o Conduct workshops, office hours, and hands on pair programming ... Hands-on with GenAI and agentic AI (LLMs, diffusion models, RAG, tool use/agents); familiarity with ...

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 ...

... GenAI-powered semantic search to enhance data accessibility and insights. • Cross-Functional ... engineering, data, compliance, and business teams to align governance strategy with enterprise ...

DevSecOps Engineer

Phoenix, AZ · On-site

$52.50 - $71.75/hr

Phoenix,AZ (Onsite) Contract Experience in DevOps, DevSecOps, Cloud Engineering, Site Reliability Engineering, or Platform Engineering experience supporting AI/ML, GenAI, Agentic AI, AgentOps, LLMOps ...

New

Development is accelerated using GenAI tools for code generation, optimization, and documentation ... Contribute to improving developer productivity and engineering excellence using AI-driven ...

Provide technical support for the GenAI and Agentic AI tools and services Qualifications * 6+ years of experience in software engineering, machine learning or GenAI, with production-grade system ...

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Genai Engineer information

What are some typical challenges a GenAI engineer faces when deploying AI models in production environments?

GenAI Engineers often encounter challenges such as ensuring model scalability, addressing bias in generated outputs, and maintaining performance consistency in real-world applications. Deploying generative AI models requires careful monitoring to prevent unexpected or inappropriate outputs, as well as efficient resource management to handle large-scale computations. Collaborating closely with data engineers, product managers, and ML operations teams is essential to streamline deployment pipelines and quickly resolve issues that arise in live environments.

What is a GenAI engineer?

A GenAI Engineer is a professional who specializes in designing, developing, and deploying generative artificial intelligence (AI) models and applications. This role involves working with advanced machine learning techniques, such as large language models and generative adversarial networks, to create systems that can generate text, images, code, or other content. GenAI Engineers collaborate with data scientists, software engineers, and product teams to integrate AI capabilities into products and services, ensuring ethical use and scalability. They also stay updated on the latest developments in AI research to continually improve model performance and effectiveness.

What is the difference between Genai Engineer vs Data Scientist?

AspectGenai EngineerData Scientist
Required CredentialsDegree in Computer Science, AI, or related fields; experience with AI/ML frameworksDegree in Data Science, Statistics, or related fields; strong programming skills
Work EnvironmentDevelops AI models, fine-tunes generative AI systems, collaborates with AI teamsAnalyzes data, builds predictive models, interprets complex datasets
Employer & Industry UsageTech companies, AI startups, research labs focusing on generative AIFinance, healthcare, marketing, and tech firms analyzing data for insights

While both roles require strong technical skills and a background in data or AI, Genai Engineers focus on developing and deploying generative AI models, whereas Data Scientists analyze data to extract insights and build predictive models. The roles often overlap but serve different primary functions within AI and data-driven organizations.

What are the key skills and qualifications needed to thrive as a GenAI engineer, and why are they important?

To thrive as a GenAI Engineer, you need expertise in machine learning, deep learning, and programming languages such as Python, along with a solid understanding of generative models like GANs and transformers. Familiarity with frameworks such as TensorFlow or PyTorch, and experience with cloud platforms and MLOps tools, are highly valuable; advanced degrees or certifications in AI or data science are often preferred. Strong problem-solving, creativity, and communication skills help GenAI Engineers design innovative solutions and effectively collaborate with multidisciplinary teams. These skills ensure the development of robust, scalable generative AI systems that address complex real-world challenges.
What are popular job titles related to Genai Engineer jobs in Arizona? For Genai Engineer jobs in Arizona, the most frequently searched job titles are:
What job categories do people searching Genai Engineer jobs in Arizona look for? The top searched job categories for Genai Engineer jobs in Arizona are:
What cities in Arizona are hiring for Genai Engineer jobs? Cities in Arizona with the most Genai Engineer job openings:
Infographic showing various Genai Engineer job openings in Arizona as of August 2026, with employment types broken down into 92% Full Time, 2% Part Time, and 6% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution.

GenAI Engineer - SRE

Dimension Consulting

Phoenix, AZ • On-site

$56.50 - $75.25/hr

Other

Posted 23 days ago


Job description

Job Titel: GenAI Engineer Location: Phoenix, AZ (Client Site – No Remote, No Virtual) Work Model: Hybrid (4 days onsite Mon-Thu, Friday remote) Interviews: 2-3 rounds (including client interview) Role Summary Seeking a GenAI Engineer to support large-scale Site Reliability Engineering (SRE), Platform Health, and Engineering Productivity initiatives. The candidate will leverage Generative AI technologies, automation frameworks, and cloud-native tooling to improve operational efficiency, incident reduction, observability, code quality, and developer productivity across enterprise platforms. The role requires close collaboration with SRE teams, platform engineering teams, application development teams, and business stakeholders to identify automation opportunities and implement AI-driven solutions. Key Responsibilities GenAI & Automation Technical Skills Python development and automation scripting Generative AI concepts and LLM integrations GitHub Copilot, Devin AI, OpenAI/Azure OpenAI ecosystem REST APIs and automation frameworks Git, CI/CD pipelines, GitHub Actions Linux/Unix administration Cloud Platforms (AWS, Azure, GCP) Terraform and Infrastructure as Code Monitoring tools such as Splunk, Dynatrace, Prometheus, Grafana, Datadog, New Relic SRE Knowledge Incident Management Problem Management Service Reliability Availability Management Operational Excellence Observability Principles Production Support