AI Engineer
Znane również jako: Artificial Intelligence Engineer · AI Developer · GenAI Engineer
Builds applications on existing AI services and language models, connects them to business data and controls the risks in their output.
The AI engineer builds working applications with available models and services, from search to an assistant inside an existing process. Unlike the machine learning engineer, this role rarely trains a model itself, since the work lies in integration, context, evaluation and covering failure behaviour. Selection gets stuck on enthusiasm about the technology, while the differentiator is setting up an evaluation that proves the application is good enough and recognising cases where the model answers convincingly but wrongly.
Kompetencje, które należy oceniać
Oto konstrukty behawioralne i kompetencyjne zawarte w tym profilu. Przy każdym z nich podano, który kwestionariusz hrmforce służy do jego pomiaru.
| Kompetencje, które należy oceniać | Poziom docelowy | hrmforce narzędzie | Metoda oceny | Kotwica behawioralna na poziomie docelowym |
|---|---|---|---|---|
| Numerical reasoning Knockout | N4 | Ability Scan | Cognitive ability test | Combines two data sources, calculates the development over time and explains which calculation step leads to which result. |
| Curiosity and exploring Kompetencje (50-ramowe): Learning Ability | N3 | Big Fifty, 15PF, Motivation | Personality questionnaire | Gathers information on new methods outside the own team and brings findings into the work meeting unprompted. |
| Dealing with ambiguity Kompetencje (50-ramowe): Flexibility | N3 | Big Fifty, Mental Resilience (4C), Competency Check | Situational Judgement Test | Formulates explicit assumptions when information is missing, proceeds on that basis and revises the approach once new data arrives. |
Krótki profil
Dziesięć najważniejszych umiejętności w tym profilu. Pełny profil zawierający wszystkie umiejętności, punkty odniesienia behawioralne i metody oceny znajduje się w pliku do pobrania.
| T | Umiejętności | Poziom docelowy | Waga | Knockout | Metoda oceny |
|---|---|---|---|---|---|
| A | Numerical reasoning | N4 | 5 | tak | Cognitive ability test |
| V | Data analysis | N4 | 5 | tak | Work sample test |
| V | Programming | N4 | 5 | tak | Work sample test |
| V | Prompting and task delegation to AI | N4 | 5 | nie | Work sample test |
| V | Evaluating and verifying AI output | N4 | 5 | nie | Work sample test |
| V | Selecting and implementing AI applications | N4 | 5 | tak | Structured interview |
| V | Critical thinking and source evaluation | N4 | 4 | nie | Work sample test |
| V | Visual communication and data storytelling | N4 | 4 | nie | Work sample test |
| V | Data visualisation | N4 | 4 | nie | Work sample test |
| V | Assessing data quality | N4 | 4 | tak | Work sample test |
Zobacz wszystkie 28 umiejętności w pełnym profilu
Narzędzia oceny dla tego stanowiska
Work sample test
Representative work sample under standardized conditions
Knowledge test (client-specific)
Professional knowledge test, customized for each client
Portfolio
Evaluation of prior work against fixed criteria
Competency Check
Behavioral-Level Competency Assessment
Ability Scan
Aptitude Test: Verbal, Numerical, and Abstract Reasoning Skills
Structured interview
Behavioral interview with a fixed structure
Big Fifty
Personality questionnaire, 150 items, 25 factors
15PF
Personality Profile, a shorter alternative to the Big Fifty
Motivation
Drivers and sources of motivation
360 Feedback
Multiple assessments based on behavioral anchors
Mental Resilience (4C)
Mental Resilience According to the 4C Model
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