A knowledge engineer is a person who builds advanced logic into computer systems with the goal of simulating human decision making. They design and develop large knowledge bases and help create expert systems to support AI capabilities. What does a knowledge engineer do? Let’s take a closer look.
Knowledge Engineering in AI
Knowledge Engineering is the branch of Artificial Intelligence (AI) that is dedicated to studying, designing, and developing systems that emulate the judgment and behavior of a human expert in a certain field.
These expert systems – as they referred to – are focused on the digitizing and automation of knowledge to resolve issues.
Expert systems are used in various fields including:
- Customer service
- Financial services
- Legal and Accounting
To break it down, the main aim behind knowledge engineering is to cut down the effort and time required to solve complex and large scale problems that would take far too long to resolve manually. It is the process of creating systems to act and take decisions regarding data in the same way a human expert in that specific field would.
The role of a knowledge engineer, therefore, is to develop these specialized expert systems by gathering the information needed and integrating it into a systematic format before deploying it for the end-users.
Knowledge engineers are also known as semantic engineers.
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Knowledge engineers are specialists who deal with expert systems that help to achieve higher levels of productivity and accuracy while being cost-efficient. The systems they develop might replace human beings and be at least so effective as humans are.
Typical examples of knowledge-based applications are:
- Diagnostics in technology and medicine
- Advice on legal and structural problems
- Configuration of technical systems
- Knowledge transfer in the form of manuals or for training purposes
Responsibilities and Duties
The responsibilities of a knowledge engineer are divided into 4 main steps. These include assessment, elicitation, structure, and validation.
The first step – assessment – starts off by first analyzing the problem at hand. Here, the engineer decides what knowledge is needed and from where.
This is followed by the second step, wherein, the knowledge is elicited. The knowledge engineer employs a number of techniques to elicit the required knowledge. Once the knowledge has been gathered, it is then structured into an expert system, a database, a knowledge base, or a knowledge asset.
The structure and format are created and then integrated with the knowledge elicited.
Finally, the knowledge engineer is responsible for the verification of the final asset and validation of the final knowledge system.
Responsibilities of a Knowledge Engineer:
- Develop, maintain and continually improve knowledge base content, taxonomy, and organization
- Interpretation of data by comparing target and actual values
- Work on processes for managing, creation, and use of knowledge
- Classification of events
- Configuration of complex systems taking different conditions into account
- Recognize the causes of errors and reduce work errors
- Support business initiatives and goals and map knowledge impacts and
- implement change/solutions
- Eliminate critical conditions by taking action
- Planning a series of actions to achieve a specific goal
- dialog-oriented, subject-specific advice to people
- Predict events based on specific events
- Work with Subject Matter experts & Data scientists
Knowledge Engineer Skills and Abilities
The role of a knowledge expert is a highly skilled one and requires a certain set of unique skills. For starters, the knowledge of computer programming languages such as Python, Java, Clojure, React, etc., is essential in this role.
In other technical requirements, a basic knowledge of LAMP stack, hardware infrastructure, and system software distribution is important.
Furthermore, working knowledge of ITIL Framework and knowledge management is also necessary.
Knowledge engineers also require soft skills to do a great job. They are problem-solvers and do great with multitasking, communication, and logical reasoning. This is important when working with large knowledge datasets. Another important skill is the ability to research and collect information. This could be from a wide variety of resources and systems.
Skills required to become a knowledge engineer:
- Strong programming language knowledge – i.e. Python, Java, etc.
- Knowledge of Database development tools and relational database concepts
- Basic knowledge of application delivery including release management
- Experience with standards-based knowledge engineering tools – ie. SQL, RDF, SPARQL, OWL, SHACL
- Knowledge of Information structure and Business intelligence (BI)
- Understanding of semantic standards and experience developing semantic models
- Foster a strong knowledge-sharing community within support
- Knowledge of Natural language processing (NLP) and the system development cycle
- Experience programming Clojure or ClojureScript or another Lisp
- Experience using RDBMS – i.e. Postgres
- Task algorithmization and Business process modeling
- Aptitude for understanding and explaining technical information
- Excellent attention to detail and natural curiosity about technology
- Ability to multitask under tight deadlines
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Educational requirements and Background
To become an efficient knowledge engineer, you’ll need to have certain educational requirements. Although a bachelor’s degree in Computer Science, IT, or Computer Applications is the basis for this role, a master’s degree is greatly valued.
Combine that with a few years of working experience in systems and applications engineering, and you will have the necessary knowledge and insight for the role of a knowledge engineer.
Often companies hiring knowledge engineers require previous experience working as a relational database administrator.
Young professionals can expect an annual salary of around $60,000. With a few years of professional experience, the average salary for a knowledge engineer is $83,000. At a senior position, the expected salary is $140,000.
How much does a knowledge engineer make?
How much does a freelance knowledge engineer earn?
The average freelance hourly rate for knowledge engineers is $62. Extrapolated to an 8-hour day, the daily rate is around $496 (freelancermap price index – as of July 2020).
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