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Generative Ai Developer Jobs in Arizona (NOW HIRING)

Stay current with emerging trends in Machine Learning, Generative AI, Agentic AI, and MLOps ... Strong Python programming with frameworks such as PyTorch, TensorFlow, or scikit-learn * Hands-on ...

... Generative AI Technical Skills 5 Technology|DevOps|Continuous delivery - Continuous deployment and release Overview The Strategic Technology Group (STG) unit at Infosys is designed for power ...

Develop and deploy Large Language Model (LLM) and Generative AI applications that improve engineering productivity, accelerate troubleshooting, and enhance knowledge discovery. * Analyze large-scale ...

AI Solution Architect

Tempe, AZ · On-site

$60.25 - $79.50/hr

Mentor engineering teams and contribute to AI architecture standards. * Support hiring and talent development for emerging AI roles. Required Qualifications * 2+ years architecting Generative AI ...

AI Engineer

Phoenix, AZ · On-site

$110K - $125K/yr

... Generative AI. • Drive discovery sprints and AI ideation efforts • Stay abreast of broad AI ... Full stack developer, Strong azure & cloud knowledge and Built applications using AI Salary Range ...

AI Engineering Leader

Tempe, AZ · On-site

$98K - $129K/yr

... Generative AI, Agentic systems, and production-grade AI platforms. This role i not a pure ... DevOps & CI/CD Design and implement CI/CD pipelines using GitHub Actions Integrate AI workflows ...

SVP AI Enterprise Architect

Tempe, AZ · On-site

$137K - $240K/yr

Mastery of Azure AI Foundry and working knowledge of AWS generative AI tools. * Strong understanding of RAG applications and advanced prompt engineering techniques. * Knowledge of tradeoffs across ...

Showing results 41-60

Generative Ai Developer information

See Arizona salary details

$17

$42

$94

How much do generative ai developer jobs pay per hour?

As of Aug 6, 2026, the average hourly pay for generative ai developer in Arizona is $42.20, according to ZipRecruiter salary data. Most workers in this role earn between $21.97 and $51.06 per hour, depending on experience, location, and employer.

What are some common challenges faced by generative AI developers when deploying models in production environments?

Generative AI Developers often encounter challenges such as ensuring model reliability, managing computational resource requirements, and addressing ethical considerations like data bias or content safety. Deploying generative models at scale requires robust monitoring to detect unexpected outputs or model drift, and collaboration with data engineers and product teams to optimize performance. Staying up-to-date with evolving frameworks and best practices is essential, as production environments demand both technical rigor and adaptability to new AI advancements.

What are the key skills and qualifications needed to thrive as a generative AI developer?

To thrive as a Generative AI Developer, you need strong programming skills (especially in Python), a deep understanding of machine learning concepts, and an advanced degree in computer science or a related field. Familiarity with frameworks like TensorFlow, PyTorch, and experience with cloud platforms or model deployment tools are typically required. Creative problem-solving, adaptability, and effective collaboration are standout soft skills in this evolving field. These abilities are crucial to design, implement, and refine generative models that solve real-world problems and drive innovation.

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

AspectGenerative Ai DeveloperMachine Learning Engineer
CredentialsBachelor's or higher in CS, AI, or related fields; experience with deep learning frameworksBachelor's or higher in CS, Data Science, or related fields; strong programming skills
Work EnvironmentDevelops AI models for content creation, chatbots, and creative applicationsBuilds and deploys ML models for various data-driven solutions across industries
Industry UsageTech, entertainment, marketing, and creative sectorsFinance, healthcare, tech, and e-commerce sectors

While both roles involve AI and machine learning, Generative Ai Developers focus on creating models that generate content, such as images or text, whereas Machine Learning Engineers develop broader ML solutions for diverse applications. The roles often overlap but differ mainly in their specific focus areas and use cases.

What is a generative AI developer?

A Generative AI Developer is a technology professional who specializes in designing, building, and deploying artificial intelligence systems that can create new content, such as text, images, audio, or code. They work with advanced machine learning models, like generative adversarial networks (GANs) or large language models, to enable computers to produce original outputs. These developers often collaborate with data scientists, researchers, and product teams to integrate AI-generated content into software applications and business solutions.
What are popular job titles related to Generative Ai Developer jobs in Arizona? For Generative Ai Developer jobs in Arizona, the most frequently searched job titles are:
What job categories do people searching Generative Ai Developer jobs in Arizona look for? The top searched job categories for Generative Ai Developer jobs in Arizona are:
What cities in Arizona are hiring for Generative Ai Developer jobs? Cities in Arizona with the most Generative Ai Developer job openings:
Infographic showing various Generative Ai Developer job openings in Arizona as of July 2026, with employment types broken down into 78% Full Time, 20% Part Time, and 2% Contract. Highlights an 64% Physical, 4% Hybrid, and 32% Remote job distribution, with an average salary of $87,783 per year, or $42.2 per hour.

Delivery Senior Consultant, Software Engineering Solutions, Identity & Gen AI Engineer

Deloitte

Gilbert, AZ

$122K - $161K/yr

Other

Re-posted 17 days ago


Deloitte rating

8.2

Company rating: 8.2 out of 10

Based on 92 frontline employees who took The Breakroom Quiz

46th of 150 rated financial services


Job description

As organizations adopt generative AI, securing how AI agents, models, and automated workflows access enterprise systems and data has become a core engineering challenge. As an Identity & Gen AI Engineer, you will build generative AI solutions with identity, access, and trust engineered in from the start, securing both human and non-human identities and governing how AI agents and GenAI platforms reach data and downstream systems. This role focuses on hands-on engineering, integration, and continuous enhancement of AI solutions in which identity and access controls are a first-class concern.

Work you'll do

As an Identity & Gen AI Engineer on the Identity and Access Management team, you will be responsible for...

Build and integrate generative AI solutions, including LLM applications, retrieval-augmented generation, and AI agents, with secure access to data and downstream systems.

Engineer authentication, authorization, and identity controls for AI agents, service accounts, and other non-human identities operating across enterprise and cloud environments.

Develop guardrails for agentic workflows, including scoped permissions, least-privilege access, credential and secrets management, and runtime policy enforcement.

Implement logging, monitoring, and governance that provide traceability and accountability for AI system actions.

Collaborate with IAM, security architecture, and data teams to embed identity controls into GenAI solution delivery and operations.

Create and maintain reference architectures, reusable patterns, and technical documentation for building and securing AI systems.

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others

The team

Our Deloitte Cyber team understands the unique challenges and opportunities businesses face in cybersecurity. Join our team to deliver powerful solutions to help our clients navigate the ever-changing threat landscape. Through powerful solutions and managed services that simplify complexity, we enable our clients to operate with resilience, grow with confidence, and proactively manage to secure success.

Our Digital Trust & Privacy offering enables trust and safety of online communications and digital products, protecting users, consumers, and patients from harm. Enables clients to provide consumer confidence in knowing with whom they are dealing and ensuring the integrity of access to data.

This opportunity sits within our Deloitte US Delivery Center model, which is dedicated to driving impactful business services. It leverages Deloitte's scale and talent, as well as a center delivery model to provide high-quality, cost-effective service with standardized processes and procedures to service businesses across Deloitte.

The Deloitte US Delivery Center has a small-business feel with a big-business impact. With the resources of Deloitte and a community feel, the delivery center model provides high-quality services to our clients. USDC professionals work out of one of our specific delivery center locations, and each location presents dynamic career opportunities for professionals to focus on their work with nominal travel requirements.

Qualifications

Required:

  • Bachelor's degree in Cybersecurity, Computer Science, Information Systems, Engineering, or a similar technical field
  • Ability to work onsite up to 5 days a week.
  • 3+ years of software engineering experience with Python or a comparable language
  • 1+ year of hands-on experience building, integrating, or deploying generative AI solutions such as large language model (LLM) applications, retrieval-augmented generation (RAG), or AI agents, including use of model APIs, orchestration frameworks, and AI development tools such as Claude Code, OpenAI Codex, GitHub Copilot, or Cursor
  • Working knowledge of identity and access management concepts and protocols, including authentication, authorization, single sign-on (SSO), and standards such as OpenID Connect (OIDC), Security Assertion Markup Language (SAML), OAuth, and JSON Web Token (JWT)
  • Ability to travel 15%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Ability to obtain and maintain the necessary security clearance. 
  • Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future.
  • Delivery Center Location & Travel Requirements:
    • Hybrid Work Model: Operate under a hybrid system requiring residence within a commutable distance to one of the US Delivery Center locations (Gilbert, Lake Mary, or Mechanicsburg) or Geo-Hub locations (Atlanta, Charlotte, Dallas, Houston, and Philadelphia)
    • Co-location Expectation: Spend up to 30% of working time co-located at an assigned office for orchestrated opportunities, including projects, practice sessions, training, and Moments That Matter at a Deloitte Delivery Center location, Geo-Hub location, approved site, or project location
    • Travel Requirement: Maximum of 10% overnight travel for client or project purposes
    • Relocation Requirement: If relocation is necessary, complete the move within 12 weeks from the start date to reside within a commutable distance

Preferred:

  • Experience deploying generative AI solutions to production environments
  • Hands-on experience with identity and access management platforms such as SailPoint, Okta, or Microsoft Entra ID
  • Experience securing non-human or machine identities, service accounts, secrets, and credentials using tools such as HashiCorp Vault or CyberArk
  • Experience with AI agent frameworks and protocols such as LangChain, LangGraph, or Model Context Protocol (MCP)
  • Experience with fine-grained authorization or policy-as-code using tools such as Open Policy Agent (OPA), Cedar, or OpenFGA
  • Familiarity with AI and LLM security risks such as the OWASP Top 10 for LLM Applications, prompt injection, and excessive agency
  • Experience applying AI governance and risk frameworks such as the NIST AI Risk Management Framework (AI RMF)
  • 2+ years of experience building or deploying workloads in cloud environments such as Amazon Web Services (AWS) and Microsoft Azure
  • Certified Information Systems Security Professional (CISSP), Certified Cloud Security Professional (CCSP), or a cloud engineering certification such as AWS Certified Solutions Architect or Microsoft Certified: Azure Solutions Architect
  • 1+ year of experience supporting federal government environments
  • 1+ year of experience with infrastructure-as-code or automation technologies such as Terraform or Ansible
Qualifications:

As organizations adopt generative AI, securing how AI agents, models, and automated workflows access enterprise systems and data has become a core engineering challenge. As an Identity & Gen AI Engineer, you will build generative AI solutions with identity, access, and trust engineered in from the start, securing both human and non-human identities and governing how AI agents and GenAI platforms reach data and downstream systems. This role focuses on hands-on engineering, integration, and continuous enhancement of AI solutions in which identity and access controls are a first-class concern.

Work you'll do

As an Identity & Gen AI Engineer on the Identity and Access Management team, you will be responsible for...

Build and integrate generative AI solutions, including LLM applications, retrieval-augmented generation, and AI agents, with secure access to data and downstream systems.

Engineer authentication, authorization, and identity controls for AI agents, service accounts, and other non-human identities operating across enterprise and cloud environments.

Develop guardrails for agentic workflows, including scoped permissions, least-privilege access, credential and secrets management, and runtime policy enforcement.

Implement logging, monitoring, and governance that provide traceability and accountability for AI system actions.

Collaborate with IAM, security architecture, and data teams to embed identity controls into GenAI solution delivery and operations.

Create and maintain reference architectures, reusable patterns, and technical documentation for building and securing AI systems.

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others

The team

Our Deloitte Cyber team understands the unique challenges and opportunities businesses face in cybersecurity. Join our team to deliver powerful solutions to help our clients navigate the ever-changing threat landscape. Through powerful solutions and managed services that simplify complexity, we enable our clients to operate with resilience, grow with confidence, and proactively manage to secure success.

Our Digital Trust & Privacy offering enables trust and safety of online communications and digital products, protecting users, consumers, and patients from harm. Enables clients to provide consumer confidence in knowing with whom they are dealing and ensuring the integrity of access to data.

This opportunity sits within our Deloitte US Delivery Center model, which is dedicated to driving impactful business services. It leverages Deloitte's scale and talent, as well as a center delivery model to provide high-quality, cost-effective service with standardized processes and procedures to service businesses across Deloitte.

The Deloitte US Delivery Center has a small-business feel with a big-business impact. With the resources of Deloitte and a community feel, the delivery center model provides high-quality services to our clients. USDC professionals work out of one of our specific delivery center locations, and each location presents dynamic career opportunities for professionals to focus on their work with nominal travel requirements.

Qualifications

Required:

  • Bachelor's degree in Cybersecurity, Computer Science, Information Systems, Engineering, or a similar technical field
  • Ability to work onsite up to 5 days a week.
  • 3+ years of software engineering experience with Python or a comparable language
  • 1+ year of hands-on experience building, integrating, or deploying generative AI solutions such as large language model (LLM) applications, retrieval-augmented generation (RAG), or AI agents, including use of model APIs, orchestration frameworks, and AI development tools such as Claude Code, OpenAI Codex, GitHub Copilot, or Cursor
  • Working knowledge of identity and access management concepts and protocols, including authentication, authorization, single sign-on (SSO), and standards such as OpenID Connect (OIDC), Security Assertion Markup Language (SAML), OAuth, and JSON Web Token (JWT)
  • Ability to travel 15%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Ability to obtain and maintain the necessary security clearance. 
  • Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future.
  • Delivery Center Location & Travel Requirements:
    • Hybrid Work Model: Operate under a hybrid system requiring residence within a commutable distance to one of the US Delivery Center locations (Gilbert, Lake Mary, or Mechanicsburg) or Geo-Hub locations (Atlanta, Charlotte, Dallas, Houston, and Philadelphia)
    • Co-location Expectation: Spend up to 30% of working time co-located at an assigned office for orchestrated opportunities, including projects, practice sessions, training, and Moments That Matter at a Deloitte Delivery Center location, Geo-Hub location, approved site, or project location
    • Travel Requirement: Maximum of 10% overnight travel for client or project purposes
    • Relocation Requirement: If relocation is necessary, complete the move within 12 weeks from the start date to reside within a commutable distance

Preferred:

  • Experience deploying generative AI solutions to production environments
  • Hands-on experience with identity and access management platforms such as SailPoint, Okta, or Microsoft Entra ID
  • Experience securing non-human or machine identities, service accounts, secrets, and credentials using tools such as HashiCorp Vault or CyberArk
  • Experience with AI agent frameworks and protocols such as LangChain, LangGraph, or Model Context Protocol (MCP)
  • Experience with fine-grained authorization or policy-as-code using tools such as Open Policy Agent (OPA), Cedar, or OpenFGA
  • Familiarity with AI and LLM security risks such as the OWASP Top 10 for LLM Applications, prompt injection, and excessive agency
  • Experience applying AI governance and risk frameworks such as the NIST AI Risk Management Framework (AI RMF)
  • 2+ years of experience building or deploying workloads in cloud environments such as Amazon Web Services (AWS) and Microsoft Azure
  • Certified Information Systems Security Professional (CISSP), Certified Cloud Security Professional (CCSP), or a cloud engineering certification such as AWS Certified Solutions Architect or Microsoft Certified: Azure Solutions Architect
  • 1+ year of experience supporting federal government environments
  • 1+ year of experience with infrastructure-as-code or automation technologies such as Terraform or Ansible
Education:Bachelor's DegreeEmployment Type:

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