Infocomm TechnologyISCO 2511
Artificial intelligence engineer
Artificial intelligence engineer apply methods of artificial intelligence in engineering, robotics and computer science to design programs which simulate intelligence including thinking models, cognitive and knowledge-based systems, problem solving, and decision making. They also integrate structured knowledge into computer systems (ontologies, knowledge bases) in order to solve complex problems normally requiring a high level of human expertise or artificial intelligence methods.
Check yourself in a minute: artificial intelligence engineer
Rate 5 of the 30 essential skills of this occupation (European ESCO data). No account needed.
digital data processing
creatively use digital technologies
use data processing techniques
design process
analyse big data
About artificial intelligence engineer
As an artificial intelligence engineer, you will design and develop sophisticated software systems that simulate human intelligence, enabling machines to perform complex reasoning, problem-solving, and decision-making tasks. Your work involves applying cutting-edge AI methodologies including machine learning, neural networks, natural language processing, and knowledge representation to create systems that can learn from data and adapt to new situations. You'll architect both the algorithmic foundations of AI systems and integrate structured knowledge into computer systems through ontologies and knowledge bases, allowing machines to process unstructured data and solve problems that typically require specialized human expertise.
Key Work Functions
Core areas of responsibility for a artificial intelligence engineer.
1
AI System Architecture and Design
- Design AI systems architectures that leverage machine learning and neural networks
- Select and implement appropriate algorithms for specific problem domains
- Design artificial neural networks with appropriate layers, activation functions, and hyperparameters
- Plan system scalability and performance optimization for production deployments
2
Data Processing and Management
- Apply digital data processing techniques to prepare data for AI model training
- Design and implement data pipelines for handling large volumes of structured and unstructured data
- Perform data mining and feature extraction to identify relevant patterns and relationships
- Categorize and structure unstructured data for model training and analysis
3
Knowledge Representation and Ontology Development
- Develop knowledge bases and ontologies to structure domain-specific information
- Integrate structured knowledge into computer systems for enhanced reasoning
- Design information extraction systems to automatically populate knowledge bases
- Implement resource description framework queries and semantic reasoning capabilities
4
Programming and Development
- Develop AI models and algorithms using Python and other programming languages
- Implement machine learning pipelines from data preparation through model deployment
- Create computer simulations for testing and validating AI systems before production
- Write clean, modular, and well-documented code following best practices
5
Business Process Modeling and Optimization
- Model business processes to identify opportunities for AI-driven automation
- Algorithmize complex business workflows for efficient computational execution
- Design task-specific algorithms that solve particular business challenges
- Develop data models that support decision-making systems and predictive analytics
6
Visualization, Testing, and Innovation
- Create visual presentations of AI model results and insights for stakeholders
- Perform rigorous testing and validation of AI systems to ensure accuracy and reliability
- Stay current with emerging AI technologies and creatively apply them to solve problems
- Conduct research on advanced AI techniques including deep learning and reinforcement learning
Do You Have the Skills for This Role?
Core competency requirements inferred from the occupation's skill profile. Take the free assessment to see how you match.
Must-Have Skills (Advanced)
Digital FluencyAdvanced
Problem SolvingAdvanced
Transdisciplinary ThinkingAdvanced
Developing PeopleAdvanced
Supporting Skills
Learning AgilityIntermediate
CommunicationIntermediate
European Skills Framework
Skills and knowledge areas required for this occupation based on European classification.
Essential (30)
digital data processingdigital data processingIdentify, locate, retrieve, store, organise and analyse digital information, judging its relevance and purpose.information structureinformation structureThe type of infrastructure which defines the format of data: semi-structured, unstructured and structured.computer simulationcomputer simulationA programme run on a computer that represents dynamic responses of a system to explore a mathematical model behaviour, using a model of a real system, composed of mathematical equations.systems development life-cyclesystems development life-cycleThe sequence of steps, such as planning, creating, testing and deploying and the models for the development and life-cycle management of a system.computer programmingcomputer programmingThe techniques and principles of software development, such as analysis, algorithms, coding, testing and compiling of programming paradigms (e.g. object oriented programming, functional programming) a...data miningdata miningThe methods of artificial intelligence, machine learning, statistics and databases used to extract content from a dataset.visual presentation techniquesvisual presentation techniquesThe visual representation and interaction techniques, such as histograms, scatter plots, surface plots, tree maps and parallel coordinate plots, that can be used to present abstract numerical and non-...algorithmsalgorithmsThe self-contained step-by-step sets of operations that carry out calculations, data processing and automated reasoning, usually to solve problems.artificial neural networksartificial neural networksA network of artificial neurons composed for solving artificial intelligence problems. These computing systems are inspired by the biological neural networks that constitute brains. Understanding of i...information extractioninformation extractionThe techniques and methods used for eliciting and extracting information from unstructured or semi-structured digital documents and sources.task algorithmisationtask algorithmisationThe techniques to convert unstructured descriptions of a process into step-by-step sequence of actions of a finite number of steps.information categorisationinformation categorisationThe process of classifying the information into categories and showing relationships between the data for some clearly defined purposes.business process modellingbusiness process modellingThe tools, methods and notations such as Business Process Model and Notation (BPMN) and Business Process Execution Language (BPEL), used to describe and analyse the characteristics of a business proce...resource description framework query languageresource description framework query languageThe query languages such as SPARQL which are used to retrieve and manipulate data stored in Resource Description Framework format (RDF).unstructured dataunstructured dataThe information that is not arranged in a pre-defined manner or does not have a pre-defined data model and is difficult to understand and find patterns in without using techniques such as data mining.Python (computer programming)Python (computer programming)The techniques and principles of software development, such as analysis, algorithms, coding, testing and compiling of programming paradigms in Python.principles of artificial intelligenceprinciples of artificial intelligenceThe artificial intelligence theories, applied principles, architectures and systems, such as intelligent agents, multi-agent systems, expert systems, rule-based systems, neural networks, ontologies an...data modelsdata modelsThe techniques and existing systems used for structuring data elements and showing relationships between them, as well as methods for interpreting the data structures and relationships.creatively use digital technologiescreatively use digital technologiesUse digital tools and technologies to create knowledge and to innovate processes and products. Engage individually and collectively in cognitive processing to understand and resolve conceptual problem...use data processing techniquesuse data processing techniquesGather, process and analyse relevant data and information, properly store and update data and represent figures and data using charts and statistical diagrams.design processdesign processIdentify the workflow and resource requirements for a particular process, using a variety of tools such as process simulation software, flowcharting and scale models.analyse big dataanalyse big dataCollect and evaluate numerical data in large quantities, especially for the purpose of identifying patterns between the data.develop creative ideasdevelop creative ideasDeveloping new artistic concepts and creative ideas.create data setscreate data setsGenerate a collection of new or existing related data sets that are made up out of separate elements but can be manipulated as one unit.analyse business requirementsanalyse business requirementsStudy clients' needs and expectations for a product or service in order to identify and resolve inconsistencies and possible disagreements of involved stakeholders.develop statistical softwaredevelop statistical softwareParticipate in the various development stages of computer programs for econometric and statistical analysis, such as research, new product development, prototyping, and maintenance.deliver visual presentation of datadeliver visual presentation of dataCreate visual representations of data such as charts or diagrams for easier understanding.apply ICT systems theoryapply ICT systems theoryImplement principles of ICT systems theory in order to explain and document system characteristics that can be applied universally to other systems.define technical requirementsdefine technical requirementsSpecify technical properties of goods, materials, methods, processes, services, systems, software and functionalities by identifying and responding to the particular needs that are to be satisfied acc...data sciencedata scienceThe field of study that deals with big amount of data using AI techniques such as machine learning algorithms to predict patterns and obtain useful information to make business decisions.
Optional (58) — show
HaskellHaskellThe techniques and principles of software development, such as analysis, algorithms, coding, testing and compiling of programming paradigms in Haskell.ErlangErlangThe techniques and principles of software development, such as analysis, algorithms, coding, testing and compiling of programming paradigms in Erlang.SAS languageSAS languageThe techniques and principles of software development, such as analysis, algorithms, coding, testing and compiling of programming paradigms in SAS language.Agile project managementAgile project managementThe agile project management approach is a methodology for planning, managing and overseeing of ICT resources in order to meet specific goals and using project management ICT tools.Ruby (computer programming)Ruby (computer programming)The techniques and principles of software development, such as analysis, algorithms, coding, testing and compiling of programming paradigms in Ruby.Common LispCommon LispThe techniques and principles of software development, such as analysis, algorithms, coding, testing and compiling of programming paradigms in Common Lisp.LispLispThe techniques and principles of software development, such as analysis, algorithms, coding, testing and compiling of programming paradigms in Lisp.Visual BasicVisual BasicThe techniques and principles of software development, such as analysis, algorithms, coding, testing and compiling of programming paradigms in Visual Basic.business intelligencebusiness intelligenceThe tools used to transform large amounts of raw data into relevant and helpful business information.Java (computer programming)Java (computer programming)The techniques and principles of software development, such as analysis, algorithms, coding, testing and compiling of programming paradigms in Java.Prolog (computer programming)Prolog (computer programming)The techniques and principles of software development, such as analysis, algorithms, coding, testing and compiling of programming paradigms in Prolog.OpenEdge Advanced Business LanguageOpenEdge Advanced Business LanguageThe techniques and principles of software development, such as analysis, algorithms, coding, testing and compiling of programming paradigms in OpenEdge Advanced Business Language.JavaScriptJavaScriptThe techniques and principles of software development, such as analysis, algorithms, coding, testing and compiling of programming paradigms in JavaScript.PerlPerlThe techniques and principles of software development, such as analysis, algorithms, coding, testing and compiling of programming paradigms in Perl.Smalltalk (computer programming)Smalltalk (computer programming)The techniques and principles of software development, such as analysis, algorithms, coding, testing and compiling of programming paradigms in Smalltalk.PHPPHPThe techniques and principles of software development, such as analysis, algorithms, coding, testing and compiling of programming paradigms in PHP.Assembly (computer programming)Assembly (computer programming)The techniques and principles of software development, such as analysis, algorithms, coding, testing and compiling of programming paradigms in Assembly.C#C#The techniques and principles of software development, such as analysis, algorithms, coding, testing and compiling of programming paradigms in C#.RRThe techniques and principles of software development, such as analysis, algorithms, coding, testing and compiling of programming paradigms in R.GroovyGroovyThe techniques and principles of software development, such as analysis, algorithms, coding, testing and compiling of programming paradigms in Groovy.SPARQLSPARQLThe computer language SPARQL is a query language for retrieval of information from a database and of documents containing the needed information. It is developed by the international standards organis...computer visioncomputer visionThe definition and functioning of computer vision. Computer vision tools to allow computers to extract information from digital images such as photographs or video. Areas of application to solve real-...Microsoft Visual C++Microsoft Visual C++The computer program Visual C++ is a suite of software development tools for writing programs, such as compiler, debugger, code editor, code highlights, packaged in a unified user interface. It is dev...TypeScriptTypeScriptThe techniques and principles of software development, such as analysis, algorithms, coding, testing and compiling of programming paradigms in TypeScript.business analyticsbusiness analyticsThe disciplines and technologies for solving business problems through employing quantitative methods such as data analysis and statistical models.Objective-CObjective-CThe techniques and principles of software development, such as analysis, algorithms, coding, testing and compiling of programming paradigms in Objective-C.database development toolsdatabase development toolsThe methodologies and tools used for creating logical and physical structure of databases, such as logical data structures, diagrams, modelling methodologies and entity-relationships.ML (computer programming)ML (computer programming)The techniques and principles of software development, such as analysis, algorithms, coding, testing and compiling of programming paradigms in ML.C++C++The techniques and principles of software development, such as analysis, algorithms, coding, testing and compiling of programming paradigms in C++.SAP R3SAP R3The techniques and principles of software development, such as analysis, algorithms, coding, testing and compiling of programming paradigms in SAP R3.Swift (computer programming)Swift (computer programming)The techniques and principles of software development, such as analysis, algorithms, coding, testing and compiling of programming paradigms in Swift.ICT project management methodologiesICT project management methodologiesThe methodologies or models for planning, managing and overseeing of ICT resources in order to meet specific goals, such methodologies are Waterfall, Incremental, V-Model, Scrum or Agile and using pro...MATLABMATLABThe techniques and principles of software development, such as analysis, algorithms, coding, testing and compiling of programming paradigms in MATLAB.LINQLINQThe computer language LINQ is a query language for retrieval of information from a database and of documents containing the needed information. It is developed by the software company Microsoft.Scratch (computer programming)Scratch (computer programming)The techniques and principles of software development, such as analysis, algorithms, coding, testing and compiling of programming paradigms in Scratch.Process-based managementProcess-based managementThe process-based management approach is a methodology for planning, managing and overseeing of ICT resources in order to meet specific goals and using project management ICT tools.lean project managementlean project managementThe lean project management approach is a methodology for planning, managing and overseeing of ICT resources in order to meet specific goals and using project management ICT tools.VBScriptVBScriptThe techniques and principles of software development, such as analysis, algorithms, coding, testing and compiling of programming paradigms in VBScript.COBOLCOBOLThe techniques and principles of software development, such as analysis, algorithms, coding, testing and compiling of programming paradigms in COBOL.Pascal (computer programming)Pascal (computer programming)The techniques and principles of software development, such as analysis, algorithms, coding, testing and compiling of programming paradigms in Pascal.deep learningdeep learningThe principles, methods and algorithms of deep learning, a subfield of artificial intelligence and machine learning. Common neural networks like perceptrons, feed-forward, backpropagation, and convolu...N1QLN1QLThe computer language N1QL is a query language for retrieval of information from a database and of documents containing the needed information. It is developed by the software company Couchbase.ScalaScalaThe techniques and principles of software development, such as analysis, algorithms, coding, testing and compiling of programming paradigms in Scala.assess ICT knowledgeassess ICT knowledgeEvaluate the implicit mastery of skilled experts in an ICT system to make it explicit for further analysis and usage.build predictive modelsbuild predictive modelsCreate models to predict the probability of an outcome.perform dimensionality reductionperform dimensionality reductionReduce the number of variables or features for a dataset in machine learning algorithms through methods such as principal component analysis, matrix factorization, autoencoder methods, and others.manage business knowledgemanage business knowledgeSet up structures and distribution policies to enable or improve information exploitation using appropriate tools to extract, create and expand business mastery.apply systemic design thinkingapply systemic design thinkingApply the process of combining systems thinking methodologies with human-centred design in order to solve complex societal challenges in an innovative and sustainable way. This is most often applied i...build recommender systemsbuild recommender systemsConstruct recommendation systems based on large data sets using programming languages or computer tools to create a subclass of information filtering system that seeks to predict the rating or prefere...identify processes for re-engineeringidentify processes for re-engineeringIdentify potential to restructure a company or part of its operations, e.g. by exploiting information technology.design database schemedesign database schemeDraft a database scheme by following the Relational Database Management System (RDBMS) rules in order to create a logically arranged group of objects such as tables, columns and processes.utilise machine learningutilise machine learningUse techniques and algorithms that are able to extract mastery out of data, learn from it and make predictions, to be used for program optimisation, application adaptation, pattern recognition, filter...design application interfacesdesign application interfacesCreate and program application interfaces, their operations, inputs and outputs and underlying types.build business relationshipsbuild business relationshipsEstablish a positive, long-term relationship between organisations and interested third parties such as suppliers, distributors, shareholders and other stakeholders in order to inform them of the orga...manage ICT semantic integrationmanage ICT semantic integrationOversee integration of public or internal databases and other data, by using semantic technologies to produce structured semantic output.CoffeeScriptCoffeeScriptThe techniques and principles of software development, such as analysis, algorithms, coding, testing and compiling of programming paradigms in CoffeeScript.operational researchoperational researchThe application of scientific methods to provide solutions to administrative and management issues of organised systems as industrial, commercial, or governmental processes.manage ICT data classificationmanage ICT data classificationOversee the classification system an organisation uses to organise its data. Assign an owner to each data concept or bulk of concepts and determine the value of each item of data.
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Frequently asked questions
What does an artificial intelligence engineer do?
Artificial intelligence engineer apply methods of artificial intelligence in engineering, robotics and computer science to design programs which simulate intelligence including thinking models, cognitive and knowledge-based systems, problem solving, and decision making. They also integrate structured knowledge into computer systems (ontologies, knowledge bases) in order to solve complex problems normally requiring a high level of human expertise or artificial intelligence methods.
What skills does an artificial intelligence engineer need?
An artificial intelligence engineer needs 30 essential skills, including digital data processing, information structure, computer simulation, systems development life-cycle, computer programming.
Will AI replace artificial intelligence engineer jobs?
The AI disruption score for artificial intelligence engineer is 77/100 (very high risk). Skills most exposed to automation: information categorisation, create data sets, information extraction. Most resilient: artificial neural networks, build business relationships, apply systemic design thinking.
AI Replacement Risk
77/ 100
Very High Risk
Low riskHigh risk
Skills most at risk from AI
Skills resilient to automation
This is the average for the whole occupation. The AI Career Shield test (about 10 minutes) shows the risk in your own work and what you can do about it.
Check your own AI riskQuick Facts
SectorInfocomm Technology
ISCO GroupInformation and communications technology professionals
Essential Skills30
Core Skills6
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