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Ai Monitoring Jobs in Wisconsin (NOW HIRING)

Senior AI Data Engineer

Wauwatosa, WI ยท On-site

$121K - $151K/yr

Establish engineering practices for reliable production AI capabilities, including security, governance, evaluation, monitoring, and operational excellence. * Apply strong data engineering and ...

Establish engineering practices for reliable production AI capabilities, including security, governance, evaluation, monitoring, and operational excellence. * Apply strong data engineering and ...

As an AI Engineer, you will independently own the end-to-end delivery of defined AI projects-from ... and monitoring-using CI/CD, containerization (Docker), and model serving. * Build reusable ...

... monitoring * Ownsystem design, tradeoffs,andlong-termscaling andmaintainability ... Strong applied AI and software engineering fundamentals * Builderswho canspantech,product,and ...

Senior AI/ML Engineer

Watertown, WI ยท On-site

$99K - $136K/yr

We are seeking a Senior AI/ML Engineer to lead the building of scalable real-time production-grade ... Integrate, deploy, fine tune and monitor models in production using cloud providers. * Set up agent ...

Senior AI/ML Engineer

Watertown, WI

$99K - $136K/yr

We are seeking a Senior AI/ML Engineer to lead the building of scalable real-time production-grade ... Integrate, deploy, fine tune and monitor models in production using cloud providers. * Set up agent ...

Senior AI/ML Engineer

Watertown, WI

$99K - $136K/yr

We are seeking a Senior AI/ML Engineer to lead the building of scalable real-time production-grade ... Integrate, deploy, fine tune and monitor models in production using cloud providers. * Set up agent ...

Senior AI/ML Engineer

Watertown, WI ยท On-site +1

$99K - $136K/yr

We are seeking a Senior AI/ML Engineer to lead the building of scalable real-time production-grade ... Integrate, deploy, fine tune and monitor models in production using cloud providers. * Set up agent ...

Our AI / ML Engineer role sits at the center of that work: building, operating, and scaling the AI ... Own the day-to-day health of agents already in production: monitor behavior, diagnose failures ...

Ensure quality, safety, and observability through monitoring, testing, guardrails, and iterative ... Actively follows AI research and emerging capabilities, applying new ideas creatively to real ...

Ensure quality, safety, and observability through monitoring, testing, guardrails, and iterative ... Actively follows AI research and emerging capabilities, applying new ideas creatively to real ...

Principal AI Engineer - AI Creator

Belgium, WI ยท On-site

$130K - $175K/yr

Ensure quality, safety, and observability through monitoring, testing, guardrails, and iterative ... Actively follows AI research and emerging capabilities, applying new ideas creatively to real ...

Ensure quality, safety, and observability through monitoring, testing, guardrails, and iterative ... Actively follows AI research and emerging capabilities, applying new ideas creatively to real ...

Ensure quality, safety, and observability through monitoring, testing, guardrails, and iterative ... Actively follows AI research and emerging capabilities, applying new ideas creatively to real ...

Showing results 41-60

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 Wisconsin as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 10% Part Time, and 4% Contract. Highlights an 92% Physical, 3% Hybrid, and 5% Remote job distribution.

Senior AI Data Engineer

Kiongroup

Wauwatosa, WI โ€ข On-site

$121K - $151K/yr

Full-time

Re-posted 11 hours ago


Job description

We are seeking a highly experienced Senior AI Data Engineer to help transform our Enterprise Data Platform into an AI-native, intelligent platform where AI agents can discover, understand, and interact with enterprise data and platform capabilities.
This role focuses on building the foundations that enable AI agents and intelligent applications to effectively leverage enterprise data, including context engineering, semantic understanding, metadata intelligence, AI-ready data abstractions, and agent-driven platform capabilities.
This is a hands-on senior role requiring deep expertise in cloud data engineering, AI-enabled data platforms, agentic AI architectures, semantic modeling, metadata and context engineering, and modern software development practices. The ideal candidate combines strong technical execution skills with architectural thinking and the ability to design and deliver scalable AI capabilities that integrate seamlessly with enterprise data platforms and business workflows.We offer:
  • Career Development
  • Competitive Compensation and Benefits
  • Pay Transparency
  • Global Opportunities

Learn More Here:https://www.dematic.com/en-us/about/careers/what-we-offer

Dematic provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.

The base pay range for this role is estimated to be $121,200.00 - $151,500.00 at the time of posting. Final compensation will be determined by various factors such as work location, education, experience, knowledge and skills.

Tasks and Qualifications:

This is What You Will do in This Role:

  • Evolve the Enterprise Data Platform into an AI-native platform by enabling intelligent discovery, understanding, and utilization of enterprise data.
  • Design and implement AI-driven capabilities and agents that enhance data platform capabilities, automate complex workflows, and improve how data is discovered, managed, governed, and consumed.
  • Build the data intelligence foundation required for AI systems, including trusted context, business understanding, and reliable access to enterprise data.
  • Design architectures that enable AI systems to reason over enterprise data and safely interact with platform capabilities, APIs, services, and enterprise applications.
  • Develop scalable AI-enabled solutions that integrate with cloud data platforms, distributed systems, and modern software architectures.
  • Establish engineering practices for reliable production AI capabilities, including security, governance, evaluation, monitoring, and operational excellence.
  • Apply strong data engineering and software engineering principles to build scalable, maintainable AI-enabled platform capabilities.
  • Partner with data, AI/ML, architecture, and product teams to identify and deliver high-impact AI capabilities for the enterprise data platform.
  • Mentor engineers and define best practices for AI-enabled data platform development.

What We are Looking For:

  • 8-12+ years of experience in enterprise software engineering, cloud data engineering, distributed systems, or data platform development.
  • Hands-on experience designing and building production AI systems, AI agents, or agentic workflows integrated with enterprise applications, APIs, and platform services.
  • Strong understanding of AI agent architectures, including tool calling, orchestration, context management, memory, evaluation, observability, and production deployment patterns.
  • Experience building AI-ready data platforms with capabilities such as semantic understanding, metadata intelligence, context engineering, and trusted data access.
  • Strong cloud data engineering experience, preferably in GCP, including BigQuery, Pub/Sub, Dataflow/Cloud Run, Composer/Airflow, and modern data platform services.
  • Strong programming skills in Python and experience building scalable software services, APIs, and microservice architectures.
  • Deep understanding of data engineering fundamentals, including data modeling, data contracts, metadata, lineage, governance, data quality, and batch/streaming architectures.
  • Experience integrating AI capabilities with enterprise data platforms and distributed systems.
  • Experience with modern data and cloud-native technologies such as Iceberg, Trino, Kubernetes, and Docker.
  • Experience designing secure, governed, and observable production AI solutions, including evaluation, monitoring, and operational excellence.

What Will Set You Apart:

  • Experience building AI agents that execute real-world enterprise workflows, beyond conversational assistants or prototypes.
  • Experience with AI frameworks and platforms such as Google ADK, Vertex AI, MCP, LangGraph, or similar technologies.
  • Experience applying RAG, embeddings, vector search, semantic layers, or knowledge graphs to enterprise AI solutions.
  • Experience with Data Mesh, domain-driven data architecture, or federated data platforms.
  • Supply chain, logistics, warehouse automation, or industrial domain experience.

Location & Authorization:This is a hybrid role requiring proximity to one of our U.S. offices (Atlanta GA, Grand Rapids MI, Milwaukee WI).Applicants must be authorized to work in the U.S. without the need for current or future sponsorship.

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