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Remote Ai Operator Jobs in Michigan (NOW HIRING)

Join a National Top Workplace Named a Top Workplace in the USA and Top Remote Workplace, Kobie is ... and operating services * 1+ years of hands-on work with LLMs in production: prompt/context ...

$12K/mo

Fully Remote within the US | Compensation: $41,600 base + $12,000 variable target Are you a proven ... AI-Native at every level: From the CEO to day-one hires, everyone builds and ships with generative ...

At Crain, we embrace AI-enabled product development as part of our operating model and are looking ... The Product Manager will work from one of the Crain offices if within commuting distance or remote ...

Senior Software Engineer, DevOps

Ann Arbor, MI · On-site +1

$160K - $190K/yr

... same capability to AI data centers, giving operators a way to better use the power already ... remote work. Our Commitments: Utilidata values the diversity of our team. We provide equal ...

Principal Data Engineer

Ann Arbor, MI · On-site +1

$170K - $210K/yr

Our Karman platform, built on a custom NVIDIA module, brings that same capability to AI data centers, giving operators a way to better use the power already available to them. We're looking for a ...

Senior Software Engineer

Detroit, MI · Remote

$121K - $159K/yr

... operated and managed. We believe the future of roadways is connected, intelligent, and designed to ... This is a fully remote, hands-on individual contributor role with meaningful ownership across core ...

Quality Assurance Analyst

Wyoming, MI · On-site +1

$55K - $65K/yr

Use approved AI-assisted tools, where appropriate, to support test planning, defect analysis ... Strong knowledge of PC and LAN environments, primarily using Windows Server and Windows operating ...

$55K - $65K/yr

Use approved AI-assisted tools, where appropriate, to support test planning, defect analysis ... Strong knowledge of PC and LAN environments, primarily using Windows Server and Windows operating ...

Quality Assurance Analyst

Three Rivers, MI · On-site +1

$55K - $65K/yr

Use approved AI-assisted tools, where appropriate, to support test planning, defect analysis ... Strong knowledge of PC and LAN environments, primarily using Windows Server and Windows operating ...

Showing results 41-60

Remote Ai Operator information

What is the difference between Remote Ai Operator vs Data Labeler?

AspectRemote Ai OperatorData Labeler
Required CredentialsBasic technical skills, sometimes certifications in AI toolsMinimal; often no formal credentials needed
Work EnvironmentRemote, tech-focusedRemote or on-site, often repetitive tasks
Industry UsageAI development, machine learning projectsData preparation for AI models
Common Search/ComparisonYesNo

Remote Ai Operators typically work on managing AI systems and require some technical knowledge, whereas Data Labelers focus on annotating data with minimal credentials. Both roles are remote and essential in AI development, but they differ in complexity and responsibilities.

How does a Remote AI Operator typically collaborate with cross-functional teams in a distributed work environment?

As a Remote AI Operator, collaboration with data scientists, engineers, and product managers is often facilitated through digital communication tools such as Slack, Zoom, and project management platforms. Regular virtual meetings and asynchronous updates are common, ensuring alignment on project goals and rapid issue resolution. Operators are expected to provide feedback on AI model performance, flag anomalies, and contribute to workflow improvements, all while adapting to different time zones and communication styles. This collaborative approach helps maintain high-quality AI system outputs and supports continuous improvement.

What are the key skills and qualifications needed to thrive as a Remote AI Operator?

To thrive as a Remote AI Operator, you need a solid understanding of artificial intelligence concepts, data processing, and typically a background in computer science or a related field. Experience with AI platforms (such as TensorFlow or PyTorch), cloud computing tools, and sometimes certifications in machine learning or data analysis are commonly required. Strong problem-solving abilities, attention to detail, and effective remote communication skills set top performers apart. These skills ensure accurate AI system management, timely troubleshooting, and seamless collaboration with distributed teams.

What is a Remote AI Operator?

A Remote AI Operator is a professional who oversees, manages, and sometimes directly interacts with artificial intelligence (AI) systems from a remote location. Their role often includes monitoring AI performance, troubleshooting issues, ensuring data integrity, and making adjustments to improve outcomes. Remote AI Operators may work in industries like customer service, manufacturing, healthcare, or autonomous vehicles. They typically use specialized software tools to interface with AI applications, ensuring the technology is operating as intended. This position often requires strong analytical skills and familiarity with AI platforms or machine learning concepts.
What are the most commonly searched types of Ai Operator jobs in Michigan? The most popular types of Ai Operator jobs in Michigan are:
What are popular job titles related to Remote Ai Operator jobs in Michigan? For Remote Ai Operator jobs in Michigan, the most frequently searched job titles are:
What cities in Michigan are hiring for Remote Ai Operator jobs? Cities in Michigan with the most Remote Ai Operator job openings:
Infographic showing various Remote Ai Operator job openings in Michigan as of August 2026, with employment types broken down into 72% Full Time, 6% Part Time, and 22% Contract. Highlights an 100% Remote job distribution.

Full-time

Re-posted 2 days ago


Job description

Join a National Top Workplace 
 
Named a Top Workplace in the USA and Top Remote Workplace, Kobie is where the best minds in loyalty come together, driven by passion and innovation. We're always looking for talented individuals who are ready to join a collaborative, growth-focused culture. As a partner to some of the world's most recognized brands, we are leaders in loyalty, helping brands build lasting emotional connections with their consumers. 
 
Join Us from Anywhere 
While our headquarters are nestled in sunny St. Petersburg, Florida, Kobie embraces a flexible work environment, offering teammates the freedom to work remotely. We understand the importance of work-life balance and support our team with: 

         Flexible Time Off to recharge when needed 
         Nine Company-Wide Holidays 
         A diverse suite of benefits prioritizing your growth, development, and personal well-being 

Discover more about our perks and benefits here. 
 
Kobie is a values-led organization where we believe that everyone is a leader, regardless of their position or role. 


About the team and what we'll build together

Kobie runs some of the largest loyalty programs in the world. We're building an internal agent platform on Amazon AgentCore that automates analyst workflows, surfaces insights from program data in Snowflake, and gives our teams and clients an LLM-native way to work with complex loyalty logic.

We're looking for a hands-on AI Engineer to ship on that platform: building agent harnesses, writing the tools those agents call, and owning the reliability and evaluation of what goes to production. This is not a research role. You'll prototype, ship, monitor, and iterate on features used by real teams

Our team tends to be people who reason carefully, ship working code,and pick up new tools without a lot of handholding. There's no single path into this role. We value the impact of what you've built and your track record of building things that hold up.

How you will make an impact

Agent Development

  • Build agent harnesses in Python using LangChain and LangGraph, including tool-calling, structured outputs (Pydantic/JSON schema), retries, streaming, and memory
  • Package agent harnesses for the AgentCore Runtime with appropriate context, tools, skills, and subagents that fit cleanly into production flows and scenarios
  • Write the tools and skills agents use  API integrations, SQL queries against Snowflake, Snowflake backed knowledge retrieval with clear contracts and Pydantic validation

Evaluation and Reliability

  • Build evaluation harnesses (golden datasets, LLM-as-judge, regression suites) using AgentCore Evaluations, and wire them into CI
  • Implement guardrails around tool execution: auth scoping, input/output validation, PII and prompt-injection protections, and hallucination mitigation
  • You own what you ship: prototype, deploy through Amazon AgentCore, monitor traces, and fix it when it breaks

Collaboration

  • Partner with data engineers on Snowflake backed retrieval patterns (Cortex Analyst and Cortex Search Services)
  • Contribute to refining our internal engineering patterns as the stack evolves

What you need to be successful

Required

  • 3+ years of professional Python, with production experience building and operating services
  • 1+ years of hands-on work with LLMs in production: prompt/context engineering, tool/function calling, structured outputs, RAG
  • Working knowledge of LangChain/LangGraph or a comparable framework like AgentCore Strands, CrewAI, or Semantic Kernel
  • Experience with LLM observability tools: Amazon CloudWatch, LangSmith, Langfuse, MLflow, or OpenTelemetry
  • Experience designing evaluation frameworks (MLFlow, DeepEval, LLM-as-judge, multi-turn regression)
  • Fluency with Git, Docker, and modern API frameworks
  • Clear written communication and the judgment to know when something is ready to ship

A bachelor's degree is not required. Equivalent practical experience: including bootcamps, self-taught work, career changes, or non-CS technical degrees counts.

Strongly Preferred

  • Hands-on experience with Amazon Bedrock and/or AgentCore as a developer: runtime, gateways, memory, policy, guardrails, observability, awscli, evaluations
  • Experience with Snowflake, Snowpark, or Snowflake Cortex
  • Fluency in writing and reading SQL, as well as understanding semantic models.
  • Familiarity with multi-agent patterns: supervisor/router, subagent/handoff, reflection, human-in-the-loop
  • A considered view on where agents should and shouldn't act and comfort pushing back when "let's add an agent" isn't the right answer
  • Experience in Loyalty, MarTech, AdTech, or a comparable data rich B2B domain
Who we are  As a trusted partner, Kobie delivers market-leading, end-to-end loyalty solutions designed to enable customer experiences for the world's most successful brands. We do this with a strategy-led technology approach that uncovers the truth behind what drives consumers on an emotional level. We believe that our team's passion and expertise are the driving forces behind our success and are proud to be named a Top Workplaces in the USA, where the best and brightest in loyalty drive our mission of growing enterprise value through loyalty. 
 
A place for all We celebrate and embrace diversity at Kobie! 
Employment at Kobie is based solely on an individual's merit and qualifications, which are directly related to professional competence. We do not discriminate against any teammate or applicant because of race,color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy, or any other characteristic protected by applicable law. 
 
We are fiercely committed to fostering a workplace where teammates can bring their authentic selves to work every day. Our DEI initiatives, including various committees, ensure that principles of equity, diversity, and inclusion are deeply ingrained throughout Kobie. While our leadership team fully supports our policy of nondiscrimination and equal opportunity, it is the responsibility of all teammates to uphold these values. 
 
Ready to join us? If you're ready to make an impact and grow in a supportive, innovative environment, we'd love to hear from you. Apply today and join the best and brightest in loyalty! 
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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