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Ai Monitoring Jobs in Arizona (NOW HIRING)

Apply AI-assisted development to code, testing, documentation, and workflow automation ... Design and operate production ETL -- ingestion, cleansing, rationalization, scheduling, monitoring

The AI Engineer is responsible for building, training, evaluating, and deploying AI/ML models and ... Monitor model performance in production; implement drift detection, feedback loops, and automated ...

The AI Engineer is responsible for building, training, evaluating, and deploying AI/ML models and ... Monitor model performance in production; implement drift detection, feedback loops, and automated ...

Manager - Application & AI Security

Scottsdale, AZ · On-site

$58.75 - $78.25/hr

Implement pipeline and artifact integrity controls and monitor production pipelines for security ... AI Security & Governance * Serve as the technical owner for enterprise AI security controls and AI ...

Apply AI-assisted development to code, testing, documentation, and workflow automation ... Design and operate production ETL -- ingestion, cleansing, rationalization, scheduling, monitoring

Deploy AI applications using Agent Engine, Cloud Run, GKE, or other appropriate GCP services ... Apply automated testing, CI/CD, logging, monitoring, tracing, evaluation, and cost-management ...

New

Preferred : • Experience with Power Platform (Power Apps, Power Automate). • Exposure to model evaluation, monitoring, and AI observability tools. • Knowledge of AI ethics and regulatory ...

AI Engineer

Mesa, AZ · On-site

$65K/yr

... Monitor, troubleshoot, and optimize AI models and data workflows for performance and scalability. • Ensure compliance with data governance, security, and privacy policies. • Stay current with the ...

... monitoring). * 2+ years leading security/compliance efforts; familiarity with enterprise security controls (IAM, encryption, secrets, audit logging) and data/privacy (PII, retention, access controls)

... model monitoring, feedback loops, and performance KPIs into product lifecycle management. • ... AI-native platform capabilities. Qualifications : Required : • 8-10 years of Product or Solution ...

Implement logging and monitoring for AI workflows including request tracing, latency tracking, and error analysis. Qualifications Need to Have * 5+ years of experience in backend or platform ...

Implement logging and monitoring for AI workflows including request tracing, latency tracking, and error analysis. Qualifications Need to Have * 5+ years of experience in backend or platform ...

Implement logging and monitoring for AI workflows including request tracing, latency tracking, and error analysis. Qualifications Need to Have * 5+ years of experience in backend or platform ...

Senior AI/ML & IVR Engineer GCP

Scottsdale, AZ · On-site

$105K - $145K/yr

As a Senior AI/ML, IVR, and GCP Engineer, you will architect, develop, and optimize advanced AI/ML ... Implement robust MLOps for model monitoring, versioning, CI/CD, retraining, and performance ...

Implement logging and monitoring for AI workflows including request tracing, latency tracking, and error analysis. Qualifications Need to Have * 5+ years of experience in backend or platform ...

Principal AI Engineer

Tucson, AZ · On-site

$179 - $226/hr

Establish platform capabilities that enable experimentation, model deployment, monitoring, observability, and continuous improvement. * Partner with IT and enterprise technology teams to ensure AI ...

Showing results 21-40

Ai Monitoring information

What is AI monitoring?

AI monitoring refers to the process of continuously observing and analyzing artificial intelligence systems to ensure they operate as intended. This includes tracking performance, detecting anomalies, ensuring compliance with ethical guidelines, and identifying potential biases or errors. Effective AI monitoring helps organizations maintain transparency, improve system reliability, and ensure that AI models make fair and accurate decisions. It is essential in applications where AI impacts critical business or societal outcomes.

What are some common challenges faced by professionals in AI monitoring roles, and how can they be addressed?

Professionals in AI Monitoring often encounter challenges such as managing large volumes of data, identifying and responding to atypical model behavior, and ensuring compliance with ethical and regulatory standards. Staying updated on the latest AI trends and best practices, utilizing robust monitoring tools, and collaborating closely with data scientists and engineers can help address these challenges. Regular training and open communication within cross-functional teams are also essential to maintain effective oversight and quickly mitigate potential issues.

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

To thrive as an AI Monitoring Specialist, you need a solid understanding of data analysis, machine learning concepts, and system monitoring, often supported by a degree in computer science or a related field. Familiarity with monitoring platforms like Datadog, Prometheus, or Splunk, as well as experience with scripting languages and AI model management tools, is typically required. Attention to detail, critical thinking, and strong communication skills help specialists identify issues quickly and collaborate with technical teams. These skills and qualities are crucial for ensuring AI systems operate reliably, securely, and efficiently in real-world applications.

What is the difference between Ai Monitoring vs Data Analyst?

AspectAi MonitoringData Analyst
Required CredentialsTypically requires knowledge of AI systems, programming, and data analysis toolsRequires statistical, analytical, and data visualization skills, often with a degree in data science or related fields
Work EnvironmentOften involves monitoring AI systems in real-time, using specialized software, in tech or AI-focused companiesAnalyzes data sets, creates reports, and provides insights, working in various industries like finance, marketing, or healthcare
Employer & Industry UsageCommon in AI development firms, tech companies, and organizations deploying AI solutionsWidely used across industries for decision-making, reporting, and strategic planning

While both roles involve working with data, Ai Monitoring focuses on overseeing AI system performance and ensuring operational accuracy, whereas Data Analysts interpret data to support business decisions. Understanding these differences helps in choosing the right career path or job search focus.

Infographic showing various Ai Monitoring job openings in Arizona as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 10% Part Time, 2% Temporary, and 4% Contract. Highlights an 92% Physical, 3% Hybrid, and 5% Remote job distribution.

Full-time

Posted 12 days ago


Job description

At Globe, our goal is to create a wonderful world for our people, business, and nation. By uniting people of passion who believe they can make a difference, we are confident that we can achieve this goal.

Job Description Build and maintain Finance application, analytics, and automation use-cases by applying AI-augmented development as part of standard delivery.
Build and maintain Finance application, analytics, and automation use-cases by applying AI-augmented development as part of standard delivery

RESPONSIBILITIES

  • Build and scale reusable data products that serve repeat demand across portfolios
  • Apply AI-assisted development to code, testing, documentation, and workflow automation
  • Design and operate production ETL -- ingestion, cleansing, rationalization, scheduling, monitoring
  • Support credit risk model work, particularly IFRS 9 ECL validation and data lineage
  • Translate business needs from Finance into technical solutions and actionable recommendations

ESSENTIAL SKILLS

  • Python and SQL at production grade -- modular code, testing, error handling
  • Software engineering fundamentals -- version control, code review, CI/CD
  • ETL and orchestration experience at production scale
  • Demonstrated AI-assisted delivery -- not just tool familiarity
  • Depth in one cloud data platform; Databricks preferred
  • Product mindset -- builds for the next user, not just the requester; documentation and handover as default

STRONG ADVANTAGE

  • Credit risk domain -- portfolio behaviour, collections, provisioning, IFRS 9 ECL
  • Telco or regulated financial services delivery
  • Platform administration across AWS, GCP, or Databricks
  • Responsible AI practice -- data classification, redaction boundaries, model governance

Equal Opportunity Employer
Globe's hiring process promotes equal opportunity to applicants, Any form of discrimination is not tolerated throughout the entire employee lifecycle, including the hiring process such as in posting vacancies, selecting, and interviewing applicants.
Globe's Diversity, Equity and Inclusion Policy Commitment can be accessed here

Make Your Passion Part of Your Profession. Attracting the best and brightest Talents is pivotal to our success. If you are ready to share our purpose of Creating a Globe of Good, explore opportunities with us.