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Ai Monitoring Jobs in Ohio (NOW HIRING)

GEA Group

$102.39 - $159.27/hr

Zur Verstärkung unseres Teams suchen wir zum nächstmöglichen Zeitpunkt einen Team Lead (m/w/d) Condition Monitoring & AI. Ihre Verantwortungsbereiche und Aufgaben: Verantwortung für die ...

LawPro.ai

OH · On-site

Monitor the LLM landscape across providers to identify deprecation timelines and suitable ... AI Pipeline Optimization: Directly implement optimizations to LLM-based orchestration pipelines for ...

Pwc

ServiceNow Deployment- Senior Associate

Toledo, OH

$77K - $202K/yr

Cloud AI Ops / AI Monitoring; and, Cloud Discovery. Travel Requirements Up to 80% Job Posting End Date The salary range for this position is: $77,000 - $202,000. Actual compensation within the range ...

Pwc

ServiceNow Deployment- Senior Associate

Columbus, OH

$77K - $202K/yr

Cloud AI Ops / AI Monitoring; and, Cloud Discovery. Travel Requirements Up to 80% Job Posting End Date The salary range for this position is: $77,000 - $202,000. Actual compensation within the range ...

helsing.ai

$80.64 - $115.19/hr

Experience deploying AI software to production including testing, quality assurance, and monitoring Join Helsing and work with world-leading experts in their fields Helsing's work is important. You ...

New

Bellwether Enterprise

AI Engineer

Cleveland, OH · On-site

Monitor and optimize performance of AI systems, ensuring quality, responsiveness, and cost efficiency in production environments. * Collaborate with AI Solutions Architect, Business Partners, and end ...

GEA Group

$79.65 - $108.10/hr

Umsetzung von Condition-Monitoring- und Analytics-Funktionen (KPIs, Anomalie-Erkennung, Diagnostik) * Entwicklung und Integration von AI- und Copilot-Funktionalitäten * Verarbeitung von IoT ...

New

Jobgether

$104 - $150/hr

You will contribute to monitoring strategies, telemetry pipelines, dashboards, and automation frameworks supporting large-scale AI environments. The role requires a strong engineering mindset, hands ...

New

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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.

What are popular job titles related to Ai Monitoring jobs in Ohio?

For Ai Monitoring jobs in Ohio, the most frequently searched job titles are:

What job categories do people searching Ai Monitoring jobs in Ohio look for?

The top searched job categories for Ai Monitoring jobs in Ohio are:

Ai Monitoring jobs near you
Infographic showing various Ai Monitoring job openings in Ohio as of August 2026, with employment types broken down into 1% As Needed, 87% Full Time, 8% Part Time, and 4% Contract. Highlights an 92% Physical, 3% Hybrid, and 5% Remote job distribution.

AI Engineer(W2 Citizens Only)

Learn Beyond Consulting LLC

Columbus, OH • On-site

Other

Posted 2 days ago

New

Job description

Job Overview

Client is seeking an experienced Agentic AI Engineer to design, develop, and support enterprise-scale AI applications that leverage agent-based architectures and large language models. This role will focus on building intelligent, autonomous systems that enhance customer experiences and drive innovation within the Chase Mobile App ecosystem.

The ideal candidate will have strong software engineering fundamentals, hands-on experience with Agentic AI frameworks, and expertise in developing production-grade AI solutions in highly regulated enterprise environments.

Key Responsibilities

Design, build, and maintain Agentic AI applications and intelligent automation solutions.
Develop and support production-grade applications using Python and Java.
Design and orchestrate multi-agent workflows, agent collaboration patterns, and autonomous decision-making systems.
Build integrations with enterprise tools, APIs, and external services.
Develop AI-powered applications leveraging large language models (LLMs), retrieval systems, and agent frameworks.
Optimize performance, scalability, and reliability of AI-enabled applications.
Implement testing, monitoring, and observability practices for AI systems in production.
Collaborate with software engineers, architects, and product stakeholders to deliver enterprise AI solutions.
Ensure adherence to responsible AI practices, security standards, and model governance requirements.
Troubleshoot and resolve issues across AI applications and supporting infrastructure.

Required Qualifications

7+ years of software engineering experience.
Strong hands-on programming experience with Python and Java.
Proven experience building, deploying, and supporting Agentic AI solutions in enterprise environments.
Hands-on experience with:
Python
Java
LangGraph
vLLM
Experience designing and managing multi-agent systems and autonomous workflows.
Strong understanding of AI application architecture, LLM integration, and retrieval-based systems.
Experience with API development, microservices architecture, and modern integration patterns.
Experience monitoring, troubleshooting, and supporting AI-enabled applications in production.
Knowledge of responsible AI principles, AI governance, security, and compliance best practices.
Strong analytical, problem-solving, and communication skills.

Preferred Qualifications

Experience working within large-scale enterprise environments.
Financial services industry experience.
Knowledge of cloud-native development and containerized applications.
Familiarity with MLOps, model lifecycle management, and AI monitoring frameworks.
Experience integrating AI solutions with enterprise software ecosystems.
Understanding of secure software development practices and SDLC methodologies.

What You''''''''ll Bring

Ability to transform business requirements into scalable AI solutions.
Passion for emerging AI technologies and agent-based systems.
Strong collaboration skills and the ability to work within cross-functional agile teams.
Experience delivering innovative, production-ready AI applications that generate measurable business value.

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