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Ai Integration Engineer Jobs in Arizona (NOW HIRING)

Globe Telecom, Inc.

AI Cloud Engineer

Globe, AZ · On-site

$53 - $70.75/hr

AI Cloud Engineer experienced in cloud platforms, primarily Google Cloud Platform (GCP) and Amazon ... AI Integration & Model Deployment * Work closely with AI teams to build and manage cloud-based ...

Globe Telecom, Inc.

Fullstack AI Engineer

Globe, AZ

Enables tight integration between application layers and machine learning models This role is ... The AI Full Stack Developer operates across the full application stack, bridging model development ...

ClifyX

AI Prompt Engineer

Chandler, AZ · On-site

... Integrate copilots with enterprise APIs, workflows, and data sources. • Implement responsible AI ... of prompt engineering frameworks and design patterns. • Hands-on experience with RAG ...

INTEL

Process Integration Engineer

Phoenix, AZ

Our work in pushing forward fields like AI, analytics, and cloud-to-edge technology is at the heart ... Working with cross-functional teams, you'll tackle complex engineering challenges and develop ...

AIAEC LLC

Senior Python Backend Engineer

Phoenix, AZ · On-site

AI Integration: Collaborate with ML engineers to deploy and scale AI models, specifically focusing on RAG (Retrieval-Augmented Generation) workflows. ? Infrastructure & DevOps: Own the lifecycle of ...

Atos

SOFTWARE ENGINEER

Phoenix, AZ · On-site

Integrate AI/ML models, LLMs, and Generative AI APIs into existing Java applications. Pipeline Engineering: Design and maintain data pipelines for machine learning model training and inference.

State Farm

Lead GenAI Engineer (LLM)

Tempe, AZ · Hybrid

$98K - $129K/yr

Build AI-Integrated APIs -- Develop and maintain robust APIs (REST, FastAPI, etc.) serving as the backbone for AI applications, orchestration, and downstream consumers * Engineer Data & Analytics ...

Infinia Search Inc

Be Seen First

Applied AI Engineer

Chandler, AZ · On-site

$60 - $95/hr

This role emphasizes reliability, auditability, and human oversight when integrating AI into engineering processes. The position is onsite in Chandler, AZ. Requirements · Bachelor's degree in ...

Intel

IP Enablement Application Engineer

Phoenix, AZ

With a focus on scalability, AI advancement, and shaping the future, we provide an unparalleled ... Key Responsibilities IP Integration & Customer Support * Provide comprehensive technical support to ...

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All JobsAi Integration Engineer JobsAi Integration Engineer Jobs in Arizona

Ai Integration Engineer information

See Arizona salary details

$41.5K

$115.8K

$161.7K

How much do ai integration engineer jobs pay per year?

As of Jul 29, 2026, the average yearly pay for ai integration engineer in Arizona is $115,810.00, according to ZipRecruiter salary data. Most workers in this role earn between $96,900.00 and $130,500.00 per year, depending on experience, location, and employer.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position such as an AI executive, senior machine learning engineer, or AI research director that offers a total compensation package including salary, bonuses, and stock options. These roles usually require advanced skills in AI, deep learning, and data science, along with extensive experience and often involve leadership responsibilities in innovative technology companies.

What are some common challenges faced by AI Integration Engineers when deploying machine learning models into existing business systems?

AI Integration Engineers often encounter challenges such as ensuring compatibility between machine learning models and legacy systems, managing data privacy and security, and optimizing model performance for real-time applications. They must also address issues related to model scalability and monitoring, as well as facilitate smooth collaboration between data science, IT, and business teams. Overcoming these challenges requires strong problem-solving skills, effective communication, and a deep understanding of both AI technologies and enterprise infrastructure.

What does an AI integration engineer do?

An AI integration engineer designs and implements systems that incorporate artificial intelligence into existing software or hardware platforms. They work with machine learning models, APIs, and data pipelines to ensure seamless integration, often using programming languages like Python and tools such as cloud services. Their role involves testing, troubleshooting, and optimizing AI components for reliable performance within broader applications.

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

To thrive as an AI Integration Engineer, you need a solid background in computer science, programming (Python, Java, or similar), and experience with AI/ML frameworks, often supported by a bachelor's degree in a related field. Familiarity with cloud platforms (such as AWS, Azure, or Google Cloud), API development, and tools like TensorFlow or PyTorch is typically required. Strong problem-solving abilities, collaboration, and clear communication are essential soft skills for bridging technical and business needs. These competencies ensure successful deployment and seamless integration of AI solutions into existing systems, driving innovation and business value.

Are AI engineers highly paid?

AI integration engineers are generally well-paid due to the high demand for expertise in artificial intelligence, machine learning, and data analysis. Salaries vary based on experience, location, and industry, but they tend to be above average compared to many other engineering roles. Advanced skills in programming, neural networks, and cloud platforms can further increase earning potential.

What is the difference between Ai Integration Engineer vs Data Scientist?

AspectAi Integration EngineerData Scientist
Required CredentialsBachelor's in CS, Engineering, or related; certifications in AI/ML toolsBachelor's or higher in CS, Statistics, or related; advanced degrees common
Work EnvironmentDeveloping and deploying AI solutions, integrating AI APIs into applicationsAnalyzing data, building predictive models, interpreting complex datasets
Employer & Industry UsageTech companies, AI service providers, software firmsResearch institutions, tech companies, finance, healthcare

While both roles involve AI, the Ai Integration Engineer focuses on implementing and integrating AI solutions into applications, whereas the Data Scientist analyzes data to develop models and insights. The roles often overlap but differ mainly in their primary focus: deployment versus analysis.

What engineer makes 500,000 a year?

Highly experienced AI Integration Engineers working in senior or specialized roles at large technology companies can earn salaries approaching or exceeding $500,000 annually, especially when including bonuses and stock options. Such compensation typically requires advanced skills in machine learning, software development, and cloud platforms, along with extensive industry experience and a strong track record of successful projects.

What are AI Integration Engineers?

AI Integration Engineers are professionals who specialize in implementing artificial intelligence solutions into existing systems, products, or workflows. They work closely with data scientists, software developers, and business teams to ensure that AI models and technologies are effectively deployed and seamlessly integrated. Their responsibilities often include customizing AI tools, developing APIs, ensuring data compatibility, and monitoring performance post-integration. These engineers play a crucial role in bridging the gap between AI research and practical business applications.
What are popular job titles related to Ai Integration Engineer jobs in Arizona? For Ai Integration Engineer jobs in Arizona, the most frequently searched job titles are:
What job categories do people searching Ai Integration Engineer jobs in Arizona look for? The top searched job categories for Ai Integration Engineer jobs in Arizona are:
What cities in Arizona are hiring for Ai Integration Engineer jobs? Cities in Arizona with the most Ai Integration Engineer job openings:
Ai Integration Engineer jobs near you
Infographic showing various Ai Integration Engineer 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 $115,810 per year, or $55.7 per hour.

AWS AI Platform Engineer

Tata Consultancy Service Limited

Phoenix, AZ • On-site

$110K - $130K/yr

Full-time

Posted 4 days ago

Job description

Senior Engineer AWS AI Platform, RAG and Agentic AI
Experience
• 1015 years of experience in Cloud Engineering, Platform Engineering, or Enterprise Architecture
• 4+ years of experience designing and implementing AI/ML and Generative AI solutions
• 2+ years of hands-on experience building RAG systems and AI Agents
• Experience working in large enterprise or financial services environments is highly preferred
Role Summary
We are seeking a Senior Engineer AWS AI Platform & RAG Integration to serve as the technical bridge between the AWS Cloud Infrastructure team, Enterprise AI Platform team, Security, Networking, Data Engineering, and Application Development teams.
The Engineering Lead will drive the onboarding of AI use cases onto the enterprise AI platform by coordinating cloud infrastructure requirements, designing scalable AI integration patterns, and implementing Generative AI solutions using AWS native AI services.
This role combines technical leadership, solution architecture, hands-on engineering, and cross-functional coordination to accelerate enterprise AI adoption while ensuring scalability, security, governance, and operational excellence.
Key Responsibilities
AI Platform Integration
• Lead onboarding of business applications onto the enterprise AI platform
• Translate business and AI requirements into AWS infrastructure and platform capabilities
• Design reusable AI integration patterns and reference architectures
• Define enterprise standards for AI application integration
• Support multiple AI initiatives across business domains
RAG and Agentic AI Development
• Design and implement Retrieval-Augmented Generation (RAG) architectures
• Build AI agents and multi-agent workflows for enterprise use cases
• Design enterprise knowledge retrieval and semantic search solutions
• Develop reusable AI orchestration components and AI APIs
• Integrate enterprise data sources into AI knowledge bases
• Implement prompt engineering and context management strategies
AWS Cloud Platform Engineering
• Work with AWS Cloud Infrastructure teams to use AI to provision and configure AWS Cloud infrastructure
• Design cloud-native AI architectures using AWS managed services
• Support infrastructure automation and deployment pipelines
• Ensure high availability, scalability, and resilience of AI workloads
• Coordinate networking, IAM, security, storage, and compute requirements
Cross-Team Leadership
• Act as the primary technical liaison between:
o AWS Cloud Infrastructure teams
o AI Platform teams
o Security and IAM teams
o Networking teams
o Data Engineering teams
o Application Development teams
o Enterprise Architecture teams
• Lead technical workshops and architecture discussions
• Coordinate cross-functional delivery activities
• Mentor engineering teams adopting AI capabilities
AI Governance and Operational Excellence
• Ensure AI solutions comply with enterprise security and governance standards
• Design secure AI integration patterns
• Implement AI guardrails and Responsible AI controls
• Support AI evaluation, monitoring, and observability
• Drive AI platform best practices and reusable accelerators
Required Technical Skills
AWS Cloud: VPC, IAM, EC2, ECS, EKS, Lambda, S3, API Gateway, CloudWatch, CloudFormation, EventBridge, SNS/SQS, Step Functions, KMS, Secrets Manager, Terraform, Elasticsearch, Cost Analysis, Budgeting
AWS AI Services: Amazon Bedrock, SageMaker AI, Amazon Knowledge Bases, Amazon OpenSearch, Amazon Titan, Bedrock Agents, Bedrock Guardrails, Textract, Comprehend, Transcribe, Rekognition, Neptune
AI Technologies: RAG architecture, Vector databases, Embeddings, Vector Search, Sematic search, Prompt engineering, Context Engineering, Agentic AI, Multi-agent orchestration, MCP, LangChain, LangGraph, LlamaIndex, AI evaluation techniques, Hallucination Mitigation Techniques, AI governance, LLM Models (Anthropic)
Programming: Python, Java, REST APIs, SDK integration, Git, CI/CD, Claude Code
Data Skills: SQL, NoSQL, Document processing, Data chunking, Metadata management, Data ingestion pipelines
Leadership Skills: Executive communication, Cross-functional coordination, Technical leadership, Architecture governance, Stakeholder management
Preferred Qualifications
• Experience with enterprise AI platform implementation
• Experience in Banking or Financial Services
• Familiarity with Responsible AI and AI Governance frameworks
• Experience implementing secure AI solutions in regulated environments
• AWS Professional or Specialty Certifications
• Experience with DevSecOps and Platform Engineering practices
Salary Range- $110,000-$130,000 a year
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