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Ai Platform Engineer Jobs in Arizona (NOW HIRING)

Troon

AI Platform Architect

Scottsdale, AZ

Partner with the Sr. Data Platform Architect on the underlying data foundation and with full stack developers on application-layer integration * Optimize performance, cost, and reliability across AI ...

Troon Golf

AI Platform Architect

Scottsdale, AZ · On-site

Partner with the Sr. Data Platform Architect on the underlying data foundation and with full stack developers on application-layer integration * Optimize performance, cost, and reliability across AI ...

Deloitte

AI Engineer Consultant

Tempe, AZ · Hybrid

Position Summary Our Deloitte Human Capital team transforms technology platforms, drives innovation, and helps make a significant impact on our clients' success. We are hiring an AI Engineer to build ...

Prologis

Lead AI Engineer

Phoenix, AZ

$147K - $202K/yr

A day in the life The Lead AI Engineer builds production AI platform capabilities that transform Prologis building, project, asset, and operational data into reusable solutions for construction ...

AURA

Principal AI Engineer

Tucson, AZ · On-site

$179K - $226K/yr

This highly visible leadership role will establish the foundational AI platforms, engineering practices, and governance framework that enable scientists, software engineers, and operations teams to ...

NSF's NOIRLab

Principal AI Engineer

Tucson, AZ · On-site

$179K - $226K/yr

This highly visible leadership role will establish the foundational AI platforms, engineering practices, and governance framework that enable scientists, software engineers, and operations teams to ...

NOAO

Principal AI Engineer

Tucson, AZ · On-site

This highly visible leadership role will establish the foundational AI platforms, engineering practices, and governance framework that enable scientists, software engineers, and operations teams to ...

Photon

AI Devs (Platform + BE)_Tempe,AZ

Anthem, AZ

Summary Photon is seeking a skilled AI Developer (Platform + Backend) to support the design, development, and implementation of AI-powered employee support platform. The enterprise AI platform built ...

Photon

AI Devs (Platform + BE)_Tempe,AZ

Anthem, AZ · On-site

Summary Photon is seeking a skilled AI Developer (Platform + Backend) to support the design, development, and implementation of AI-powered employee support platform. The enterprise AI platform built ...

Virtuous

Lead Data Platform Engineer

Phoenix, AZ · On-site

$101K - $134K/yr

They are seeking a Lead Data Platform Engineer to design and build a robust data ecosystem that supports AI-enabled workflows and ensures data governance across the organization. Responsibilities ...

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All JobsAi Platform Engineer JobsAi Platform Engineer Jobs in Arizona

Ai Platform Engineer information

See Arizona salary details

$30

$59

$88

How much do ai platform engineer jobs pay per hour?

As of Aug 9, 2026, the average hourly pay for ai platform engineer in Arizona is $59.60, according to ZipRecruiter salary data. Most workers in this role earn between $47.02 and $68.75 per hour, depending on experience, location, and employer.

What is an AI Platform Engineer?

AI Platform Engineers are technology professionals who design, build, and maintain the infrastructure that supports the development, deployment, and scaling of artificial intelligence (AI) and machine learning (ML) models. They work closely with data scientists and software engineers to ensure that AI solutions can run efficiently and securely in production environments. Their responsibilities often include managing cloud or on-premises platforms, automating workflows, and implementing best practices for model versioning, monitoring, and resource optimization.

How does an AI Platform Engineer typically collaborate with data scientists and software engineers in a project environment?

AI Platform Engineers often serve as a bridge between data scientists and software engineers, ensuring that machine learning models are seamlessly integrated into scalable, production-ready systems. They work closely with data scientists to understand model requirements and deployment needs, and with software engineers to embed these models within applications and services. This collaboration involves frequent communication, joint troubleshooting, and participation in code reviews to maintain a robust and efficient AI infrastructure.

What is the difference between Ai Platform Engineer vs Data Engineer?

AspectAi Platform EngineerData Engineer
CredentialsBachelor's in CS, AI, or related; experience with cloud platformsBachelor's in CS, Data Science, or related; experience with databases and ETL tools
Work EnvironmentDeveloping AI infrastructure, deploying ML models, working with cloud servicesBuilding data pipelines, managing data storage, ensuring data quality
Industry UsageTech companies, AI startups, cloud providersFinance, healthcare, e-commerce, any data-driven industry

While both roles involve working with data and cloud platforms, Ai Platform Engineers focus on building and maintaining AI infrastructure and deploying machine learning models. Data Engineers primarily develop data pipelines and manage data storage. The roles often collaborate but serve different core functions within AI and data ecosystems.

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

To thrive as an AI Platform Engineer, you need strong programming skills (especially in Python and Java), a background in computer science or related fields, and experience with machine learning frameworks. Familiarity with cloud platforms (like AWS, Azure, or GCP), containerization tools (Docker, Kubernetes), and CI/CD systems is typically required, along with certifications such as Google Cloud Professional Machine Learning Engineer. Excellent problem-solving, collaboration, and communication skills help you integrate AI solutions across teams and projects. These competencies ensure the efficient development, deployment, and maintenance of scalable AI systems in dynamic production environments.
What are popular job titles related to Ai Platform Engineer jobs in Arizona? For Ai Platform Engineer jobs in Arizona, the most frequently searched job titles are:
What job categories do people searching Ai Platform Engineer jobs in Arizona look for? The top searched job categories for Ai Platform Engineer jobs in Arizona are:
What cities in Arizona are hiring for Ai Platform Engineer jobs? Cities in Arizona with the most Ai Platform Engineer job openings:
Ai Platform Engineer jobs near you
Infographic showing various Ai Platform Engineer job openings in Arizona as of August 2026, with employment types broken down into 33% Full Time, 33% Part Time, and 34% Contract. Highlights an 67% In-person, and 33% Remote job distribution, with an average salary of $123,965 per year, or $59.6 per hour.

AWS AI Platform Engineer

Tata Consultancy Service Limited

Phoenix, AZ • On-site

$110K - $130K/yr

Full-time

Re-posted 15 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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