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Ai Automation Engineer Jobs in Michigan (NOW HIRING)

AI Engineer - On Site

Grand Rapids, MI · On-site

$110 - $150/hr

Role Overview The AI Automation Engineer is a core technical delivery resource within K Group's AI and Automation practice. Working alongside the AI Enablement Team and practice leadership, this role ...

Role Overview The AI Automation Engineer is a core technical delivery resource within K Group's AI and Automation practice. Working alongside the AI Enablement Team and practice leadership, this role ...

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Role Overview The AI Automation Engineer is a core technical delivery resource within K Group's AI and Automation practice. Working alongside the AI Enablement Team and practice leadership, this role ...

Job Purpose The Senior Finance AI & Automation Developer's primary responsibilities are to design, build, & deploy automation and AI-driven solutions across Finance processes. These projects will ...

Business Process Automation Engineer Full Time Professional ANN ARBOR, MI, US 15 days ago ... AI/OCR document processing experience * Familiarity with finance operations and reconciliation ...

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... AI Tools), and QUIP Keywords Automotive, Test Automation, Python, CAN About Cognizant's IoT ... Within Cognizant IOT, we engineer industry‑aligned, IoT‑enabled products that merge industry ...

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Showing results 21-40

Ai Automation Engineer information

See Michigan salary details

$32.2K

$93.4K

$142.1K

How much do ai automation engineer jobs pay per year?

As of Aug 21, 2026, the average yearly pay for ai automation engineer in Michigan is $93,371.00, according to ZipRecruiter salary data. Most workers in this role earn between $75,400.00 and $107,600.00 per year, depending on experience, location, and employer.

What is an AI automation engineer?

AI Automation Engineers are professionals who design, develop, and implement artificial intelligence solutions to automate tasks and workflows within organizations. They combine expertise in AI, machine learning, and software engineering to create systems that can perform repetitive or complex tasks efficiently with minimal human intervention. Their work often involves building and integrating AI models, optimizing processes, and ensuring the reliability and scalability of automated solutions. These engineers collaborate closely with data scientists, software developers, and business stakeholders to align automation initiatives with organizational goals.

What skills and qualifications are needed to thrive as an AI automation engineer?

To thrive as an AI Automation Engineer, you need strong programming skills (such as Python), a solid understanding of machine learning concepts, and typically a degree in computer science, engineering, or a related field. Familiarity with automation frameworks, cloud platforms (like AWS, Azure, or GCP), and machine learning libraries (such as TensorFlow or PyTorch) is often required. Problem-solving ability, adaptability, and effective communication are crucial soft skills for collaborating across teams and addressing complex technical challenges. These skills ensure the successful design, implementation, and scaling of automated AI solutions that drive business efficiency and innovation.

What are common challenges faced by AI automation engineers during project implementation?

AI Automation Engineers often encounter challenges such as integrating new AI models with existing legacy systems, ensuring data quality for accurate model outputs, and managing stakeholder expectations regarding automation outcomes. They must also address issues related to model scalability and robustness, especially when deploying solutions in dynamic production environments. Collaboration with cross-functional teams—including data scientists, software engineers, and business analysts—is essential to navigate these complexities and deliver effective automation solutions.

What is the difference between Ai Automation Engineer vs Data Scientist?

AspectAi Automation EngineerData Scientist
Required CredentialsBachelor's in Computer Science, Engineering, or related field; knowledge of AI, automation toolsBachelor's or higher in Statistics, Computer Science, or related; strong analytical skills
Work EnvironmentTech companies, automation firms, R&D labs; focus on developing AI-driven automation solutionsData analysis teams, research institutions; focus on data modeling and insights
Employer & Industry UsageUsed in manufacturing, software development, AI startupsUsed across finance, healthcare, marketing, and tech sectors
Common Search & Comparison IntentUnderstanding roles in AI automationExploring data analysis careers

While both roles involve working with data and AI, Ai Automation Engineers focus on developing automated AI systems and integrating AI into processes. Data Scientists analyze data to extract insights and build models. The roles overlap in AI knowledge but differ in application and focus areas.

Is AI automation a high paying job?

AI automation engineers typically earn higher-than-average salaries due to their specialized skills in machine learning, programming, and data analysis. Salaries vary based on experience, location, and industry, but the role is generally considered well-compensated within the tech field.

Is AI automation engineer in demand?

AI automation engineers are in high demand due to the increasing adoption of artificial intelligence and automation across industries. They are needed to develop, implement, and maintain AI-driven systems, often requiring skills in machine learning, programming, and data analysis. Job opportunities are growing as companies seek to improve efficiency and innovation through automation technologies.

What job categories do people searching Ai Automation Engineer jobs in Michigan look for?

The top searched job categories for Ai Automation Engineer jobs in Michigan are:

What cities in Michigan are hiring for Ai Automation Engineer jobs?

Cities in Michigan with the most Ai Automation Engineer job openings:

Infographic showing various Ai Automation Engineer job openings in Michigan as of August 2026, with employment types broken down into 73% Full Time, 21% Part Time, 2% Temporary, 3% Contract, and 1% Nights. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution, with an average salary of $93,371 per year, or $44.9 per hour.

AI Engineer - On Site

K Group Companies

Grand Rapids, MI • On-site

$110 - $150/hr

Other

Posted 6 days ago


Job description

About K Group Companies

K Group Companies is a locally owned and operated master integrator headquartered in Grand Rapids, Michigan, with a proud history dating back to 1980. We support customers across the United States by delivering innovative, high-quality technology solutions across managed IT, physical security, and integrated services.

As a third-generation, family-owned business, we’ve built our reputation on long-term relationships, trusted expertise, and a commitment to doing things the right way for our customers and for each other.

We believe great work happens when people feel connected to their purpose, their team, and their growth.

Work Authorization Requirement: Applicants must be legally authorized to work in the United States at the time of application. This position does not offer employment visa sponsorship now or in the future. This role is 100% onsite in Grand Rapids, Michigan. No third-party recruiters, agencies, or C2C arrangements.

Why K Group Companies?

At K Group Companies, culture is built on long-standing relationships, both with our customers and with each other.

Our team is made up of people who take pride in solving problems, supporting one another, and delivering work that reflects the standards we’ve built our reputation on. Whether it’s designing secure environments for customers, supporting critical IT infrastructure, or collaborating across teams, we operate as one organization working toward shared success.

We also believe work should be fulfilling and enjoyable. From friendly gaming competitions in our Team Zone arcade to grabbing lunch together in the community, we value connection and teamwork just as much as technical excellence.

What you can expect here:
  • A family-owned company with deep roots in West Michigan
  • A trusted advisor culture built over 40+ years of relationships
  • The opportunity to work across diverse, real-world technology environments
  • A team-oriented culture grounded in accountability, collaboration, and pride in workmanship
  • A workplace where people genuinely know and support each other

We believe we are better together, and that belief shows up in everything we do.

Role Overview

The AI Automation Engineer is a core technical delivery resource within K Group’s AI and Automation practice. Working alongside the AI Enablement Team and practice leadership, this role leads the design, build, and ongoing optimization of AI-powered solutions for both internal operations and external client engagements. The engineer translates scoped strategy into production-grade systems, contributes to internal adoption efforts, and helps build the repeatable frameworks that allow the practice to scale.

This is a builder role first. The ideal candidate thrives on turning complex business requirements into working, measurable systems — and takes pride in delivering solutions that are practical, responsible, and built to last.

Core Responsibilities Automation & Workflow Engineering
  • Design, build, and maintain AI-powered automation workflows using n8n, Python, and integrated APIs including ConnectWise, Microsoft 365, SharePoint, and others.
  • Develop intelligent systems including multi-stage AI classification pipelines, automated compliance and billing review processes, and notification-driven monitoring tools.
  • Implement provider-abstracted AI architectures supporting OpenAI, Ollama, and other LLM providers with configurable confidence thresholds and fallback logic.
  • Build and iterate on internal tools that reduce manual effort, improve data accuracy, and create measurable operational efficiencies.
Client Delivery & Engagement Support
  • Lead delivery execution for AI/automation client engagements — managing implementation, iteration, and ongoing optimization through to completion in coordination with the practice team.
  • Participate in client discovery sessions as a technical resource, contributing to needs assessment, feasibility evaluation, and solution design under the direction of practice leadership.
  • Translate scoped business requirements into working systems and present delivery results to client stakeholders including operations leads and project sponsors.
  • Build reusable delivery frameworks, templates, and documentation that allow AI consulting engagements to scale efficiently across multiple clients.
Enablement & Adoption
  • Support AI adoption across internal teams by building training materials, playbooks, and purpose-built tools that make AI accessible to non-technical staff.
  • Track and report on AI adoption metrics, connecting usage data to business outcomes rather than vanity metrics.
  • Contribute to responsible AI use and utilization efforts — including Microsoft 365 Copilot — supporting the governance frameworks and usage guidelines established by practice leadership.
What Success Looks Like — Year One

To be defined collaboratively with leadership. Initial indicators may include:

  • Production-grade automation workflows deployed for internal K Group operations.
  • Client delivery engagements completed on time and within scope with documented outcomes.
  • Reusable delivery frameworks and templates in place for at least two service offering types.
  • AI adoption metrics established and actively tracked across internal teams.
  • Contributed to AI utilization efforts, including Microsoft 365 Copilot, with adoption measurably improving across internal teams.
Experience & Qualifications
  • Hands-on expertise in AI/automation platforms — n8n, LLM integrations, workflow orchestration, API development.
  • Proficiency with Python and modern integration patterns across business platforms including ConnectWise, Microsoft 365, and SharePoint.
  • Experience building production-grade systems — not just proof-of-concept tools — with attention to reliability, documentation, and maintainability.
  • Strong communicator capable of presenting technical work and outcomes to non-technical stakeholders.
  • Comfortable working within a defined strategic framework while exercising autonomy in execution and delivery decisions.
  • MSP or technology services background preferred.
Reporting & Structure

Reports to: Director of Engineering

Team: AI Enablement Team

Location: Grand Rapids, MI

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