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Knowledge Engineering Jobs in Michigan (NOW HIRING)

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Entry Level Controls Engineer

Detroit, MI · On-site

$82K - $106K/yr

Degree in a Technical Field, related to Engineering or Systems * Excellent communication and ... Manufacturing process knowledge or building/facility management knowledge * Programmable Logic ...

Magna

Global Business Development Manager

Troy, MI · On-site

Special Knowledge - Engineering, product design and manufacturing, business case development and analysis. Excellent verbal and written communication skills. An internationalist, able to complete ...

Magna

Global Business Development Manager

Troy, MI · On-site

Special Knowledge - Engineering, product design and manufacturing, business case development and analysis. Excellent verbal and written communication skills. An internationalist, able to complete ...

androidind

Engineering Intern

Warren, MI

$15.75 - $20.50/hr

ENGINEERING INTERN JOB SUMMARY: We have an opportunity for an Engineering Intern at our Avancez ... Knowledge of Lean principles is preferred * Develop Process Failure Mode Effects and Analysis in a ...

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Knowledge Engineering information

What does a knowledge engineer do?

A knowledge engineer designs, develops, and maintains systems that capture and organize knowledge for artificial intelligence and expert systems. They analyze information, create ontologies, and use tools like knowledge bases and reasoning algorithms to enable machines to simulate human decision-making. Strong skills in logic, data modeling, and programming are essential for this role.

What is knowledge engineering?

Knowledge engineering is a field within artificial intelligence that focuses on creating systems capable of simulating human decision-making and reasoning. It involves gathering, organizing, and structuring information so that computers can use it to solve complex problems. Knowledge engineers work to build knowledge bases and rule-based systems, often collaborating with domain experts to codify expertise into a form that machines can process. This discipline is fundamental in the development of expert systems, intelligent agents, and modern AI applications.

What engineers make $500,000 a year?

Highly experienced engineers in specialized fields such as software engineering, data engineering, or systems architecture can earn $500,000 or more annually, especially in senior or executive roles at large technology companies. These positions often require advanced skills, certifications, and extensive industry experience, and may include bonuses and stock options that contribute to total compensation.

What is the difference between Knowledge Engineering vs Data Scientist?

AspectKnowledge EngineeringData Scientist
Required CredentialsTypically degrees in computer science, AI, or related fields; certifications in knowledge systemsDegrees in statistics, computer science, or mathematics; certifications in data analysis or machine learning
Work EnvironmentDeveloping knowledge bases, expert systems, and AI applications in tech or research settingsAnalyzing data, building predictive models, and deriving insights in various industries
Employer & Industry UsageUsed in AI development, research institutions, and tech companiesUsed across finance, healthcare, marketing, and tech sectors

While both roles involve working with data and AI, Knowledge Engineers focus on creating structured knowledge bases and expert systems, whereas Data Scientists analyze data to extract insights and build predictive models. Understanding these differences helps in choosing the right career path or job focus.

How does a Knowledge Engineer typically collaborate with subject matter experts during a project?

Knowledge Engineers frequently work closely with subject matter experts (SMEs) to extract, structure, and formalize domain knowledge into usable formats for AI systems or knowledge bases. This collaboration often involves conducting interviews, facilitating workshops, and reviewing documentation to ensure complex concepts are accurately captured. Effective communication and iterative feedback are key, as Knowledge Engineers must bridge the gap between technical requirements and expert insights. This teamwork helps ensure that the resulting system is both technically sound and aligned with real-world practices.

What engineers make 200,000 a year?

Senior knowledge engineers, especially those with expertise in artificial intelligence, machine learning, and data science, can earn $200,000 or more annually. High salaries are often associated with extensive experience, advanced certifications, and working in industries like technology, finance, or consulting, typically in roles involving complex problem-solving and specialized tools.

How much does a knowledge engineer make?

A knowledge engineer's salary typically ranges from $70,000 to $130,000 annually, depending on experience, education, and location. Senior roles or those with specialized skills in AI, machine learning, or data management can earn higher salaries. Many positions require proficiency with knowledge representation, ontologies, and tools like Protégé or OWL.

What are the key skills and qualifications needed to thrive as a Knowledge Engineer, and why are they important?

To thrive as a Knowledge Engineer, you need a strong background in computer science, logic, and data modeling, often supported by a relevant degree. Familiarity with knowledge representation systems, ontologies, semantic web technologies, and tools like Protégé is typically required, along with experience in programming languages such as Python or Java. Strong analytical thinking, problem-solving abilities, and clear communication skills help you collaborate with subject matter experts and translate complex information into structured formats. These skills are critical for building effective knowledge-based systems that drive intelligent decision-making and organizational efficiency.
What are popular job titles related to Knowledge Engineering jobs in Michigan? For Knowledge Engineering jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Knowledge Engineering jobs in Michigan look for? The top searched job categories for Knowledge Engineering jobs in Michigan are:
What cities in Michigan are hiring for Knowledge Engineering jobs? Cities in Michigan with the most Knowledge Engineering job openings:
Knowledge Engineering jobs near you
AI Knowledge Content Specialist

AI Knowledge Content Specialist

InDepth Engineering Solutions, LLC

Auburn Hills, MI • On-site, Remote

$33 - $35/hr

Full-time

Posted 7 days ago

Job description

The Instructional Designer / Knowledge Content Specialist is responsible for designing, structuring, and maintaining clear, user-centered process documentation and knowledge assets. This role transforms complex processes into intuitive, actionable content for both internal employees and customer-facing channels, including AI-powered tools.
This individual ensures that all knowledge artifacts—such as SOPs, work instructions, decision trees, and bot content—are accurate, accessible, and aligned with business processes, enabling end users to quickly find and apply the right information.
Key Responsibilities
- Process Documentation & Knowledge Development
- Develop and maintain human-readable Standard Operating Procedures (SOPs) and Work Instructions (WIs)
- Translate complex workflows into clear, structured, and easy-to-follow content
- Ensure documentation aligns with process maps and operational intent
- Apply ISO-aligned document control standards (versioning, ownership, updates)
AI & Customer-Facing Content Design
- Create and optimize content for AI chatbots and virtual assistants
- Design responses that are:
- Clear and conversational
- Accurate and compliant
- Aligned with brand voice and customer expectations
- Ensure content supports self-service and first-contact resolution
Decision Tree & Guided Experience Design
- Develop decision trees, guided workflows, and troubleshooting logic
- Structure content to help agents and customers:
- Navigate complex scenarios
- Make accurate decisions quickly
- Collaborate with SMEs to validate logic and edge cases
Knowledge Strategy & User Experience
- Design content with a user-first mindset (agents, customers, partners)
- Improve findability and usability of knowledge assets
- Standardize formats, templates, and naming conventions
- Identify gaps and continuously improve knowledge effectiveness
Process-to-Content Translation Expertise
Proven ability to take complex processes and convert them into clear, structured SOPs, work instructions, or knowledge content that are easy to follow.
Content Optimization & Simplification Skills
Demonstrated experience improving, streamlining, and enhancing existing documentation for clarity, usability, and efficiency (human + AI consumption).
User-Centered & AI-Ready Content Design
Ability to create content tailored to different audiences (agents, customers, chatbots) with a focus on usability, logical flow, and self-service success.
Experience with AI/chatbot content or knowledge platforms
Portfolio or writing samples showcasing structured documentation
Background in instructional design, technical writing, or knowledge management

Requirements
Bachelor's Degree is preferred; however, candidates with strong relevant experience may still be considered.
Role is highly focused on Project Elevate and AI-related transformation initiatives
Open to candidates from any industry background with strong content development and documentation expertise
Candidates should be prepared to discuss prior writing experience and provide examples of SOPs, work instructions, process documentation, or similar structured content
Writing samples are preferred prior to the interview and will be requested during the interview process
Virtual interview process consisting of behavioral, experience-based, and content evaluation discussions
Candidates may be asked to review existing documentation and explain how they would improve readability, streamline content, and enhance usability
Experience with AI tools is beneficial; direct chatbot development experience is not required, but candidates should be comfortable discussing how AI-generated content can improve user experience
Experience with Visio and Salesforce is preferred but not required