Skills & Competencies for Principal AI Engineer

Principal AI Engineer job profile

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JOB SUMMARY for Principal AI Engineer

Designs and develops scalable solutions using AI tools and machine-learning models.

JOB RESPONSIBILITIES for Principal AI Engineer

Performs research and testing to develop machine learning algorithms and predictive models. Utilizes big data computation and storage tools to create prototypes and datasets. Conducts model training and evaluation. Integrates, tests, tunes, and monitors solutions. Proficient with multiple AI tools such as Python, Java, or R and machine learning frameworks like Spark, TensorFlow, or sciket-learn.

Principal AI Engineer SALARY RANGE

BASE 50%
$152,817
TOTAL 50%
$165,429
Job Level
P04
Job Code
IT10000585
Education/Degree
Master's Degree or MBA
Reports To
Manager or Head of a Unit/Department

Principal AI Engineer Skills and Competencies List

Proficiency Levels and Behavioural Indicators
Salary.com identifies five increasing levels of proficiency for each skill/competency. Some jobs require only a relatively low level of proficiency in each skill/competency, while other jobs will require a more advanced level of proficiency in the same skill/competency. These levels rate the degree of proficiency (skill level, expertise) we expect the incumbent to perform in the given skill/competency for the given job. Note that we intentionally do not associate timeframes or years of experience in performing the skill/competency because that can be misleading. Proficiency levels identify what the incumbent knows and can do rather than how long they have been doing it. Also, note that the proficiency levels are cumulative, e.g., a level 4 proficiency implies the ability to perform all the behaviors at the lower levels.
Check each Principal AI Engineer skill and competencie below to view definitions.
INDUSTRY COMPETENCIES JOB FAMILY COMPETENCIES CORE COMPETENCIES
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8 hard skills or competencies (industry competencies) for Principal AI Engineer

1 Industry Competency – Software Engineering
Proficiency Level -4
Skill definition-Applying computer science and engineering principles, methods, and practices to design, develop, deploy, and maintain reliable software systems.
Level 1 Behaviors
(General Familiarity)
Defines the concepts, components, and methodologies used in software engineering.
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Level 2 Behaviors
(Light Experience)
Follows established guidelines and standards when carrying out basic software maintenance tasks.
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Level 3 Behaviors
(Moderate Experience)
Operates complex quality assurance tools to test and evaluate software products before deployment.
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Level 4 Behaviors
(Extensive Experience)
Directs the implementation of testing procedures to improve the usability of software products.
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Level 5 Behaviors
(Mastery)
Designs and builds news software engineering tools to drive efficiency in operations.
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2 Industry Competency – Artificial Intelligence (AI)
Proficiency Level -4
Skill definition-Applying the technologies and methodologies of artificial intelligence(AI) to develop and implement AI products and services for various business goals.
Level 1 Behaviors
(General Familiarity)
Describes the importance and goals of artificial intelligence (AI) across businesses and organizations.
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Level 2 Behaviors
(Light Experience)
Compiles reports and assessments on data and AI capability requirements for senior management's review.
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Level 3 Behaviors
(Moderate Experience)
Consults with managers to determine and refine machine learning objectives.
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Level 4 Behaviors
(Extensive Experience)
Evaluates advanced statistical techniques using AI methods to advance knowledge and pursue new approaches.
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Level 5 Behaviors
(Mastery)
Creates machine learning algorithms to analyze vast volumes of historical data to make predictions.
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3 Principal AI Engineer - Skill and Competency
Proficiency Level - 3
4 Skill and Competency - Principal AI Engineer
Proficiency Level - 4
5 Competency for - Principal AI Engineer
Proficiency Level - 5

5 general skills or competencies (Job family competencies) for Principal AI Engineer

1 Job Family Competencies – Cloud Computing
Proficiency Level -3
Skill definition-Providing on-demand computing services that allow users to store, manage, and process their data remotely.
Level 1 Behaviors
(General Familiarity)
Cites security solutions for cloud-based computing.
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Level 2 Behaviors
(Light Experience)
Assists with transitioning cloud computing databases and software as a service technology.
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Level 3 Behaviors
(Moderate Experience)
Completes the architecture assessments of new computing solutions within public cloud services.
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Level 4 Behaviors
(Extensive Experience)
Evaluates cloud computing architectures to drive cost reduction in managing IT systems.
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Level 5 Behaviors
(Mastery)
Conceptualizes new IT cloud computing products and service offerings to drive business continuity.
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2 Job Family Competencies – Deep Learning
Proficiency Level -4
Skill definition-Analyzing, developing, and applying big data and algorithms to imitate how humans think and learn.
Level 1 Behaviors
(General Familiarity)
Describes the concepts and fundamental statistics of deep learning.
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Level 2 Behaviors
(Light Experience)
Conducts research to identify cutting-edge techniques and tools in deep learning.
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Level 3 Behaviors
(Moderate Experience)
Deploys accurate deep learning models to support computer vision tasks.
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Level 4 Behaviors
(Extensive Experience)
Creates and leverages deep learning models to improve the effectiveness of our business operations.
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Level 5 Behaviors
(Mastery)
Champions the adoption of advanced tools in developing language models to solve complex deep learning problems.
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3 Principal AI Engineer - Skill and Competency
Proficiency Level - 3
4 Skill and Competency - Principal AI Engineer
Proficiency Level - 4
5 Competency for - Principal AI Engineer
Proficiency Level - 5

9 soft skills or competencies (core competencies) for Principal AI Engineer

1 Core Competencies – Innovation
Proficiency Level -4
Skill definition-The ability and process of implementing new ideas and initiatives to improve organizational performance.
Level 1 Behaviors
(General Familiarity)
Describes the market conditions that impact the business.
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Level 2 Behaviors
(Light Experience)
Collects and compiles competitor information for competitive analysis.
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Level 3 Behaviors
(Moderate Experience)
Applies technical expertise, business sense, and product knowledge to manage the product lifecycle effectively.
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Level 4 Behaviors
(Extensive Experience)
Coordinates technical and business teams to solve complex and diverse customer problems.
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Level 5 Behaviors
(Mastery)
Builds strong business partnerships internally and externally to drive "win-win" business successes.
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2 Core Competencies – Attention to Detail
Proficiency Level -4
Skill definition-Executing and completing a task with a high level of accuracy.
Level 1 Behaviors
(General Familiarity)
Explains why attention to detail plays an important role in own function or unit.
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Level 2 Behaviors
(Light Experience)
Performs assigned responsibilities according to standard procedures and standards.
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Level 3 Behaviors
(Moderate Experience)
Implements a variety of cross-checking approaches and mechanisms.
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Level 4 Behaviors
(Extensive Experience)
Demonstrates expertise in quality assurance tools, techniques, and standards.
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Level 5 Behaviors
(Mastery)
Designs techniques for measuring the cost and impact of errors.
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3 Principal AI Engineer - Skill and Competency
Proficiency Level - 3
4 Skill and Competency - Principal AI Engineer
Proficiency Level - 4
5 Competency for - Principal AI Engineer
Proficiency Level - 5

Summary of Principal AI Engineer skills and competencies

There are 8 hard skills for Principal AI Engineer, Software Engineering, Artificial Intelligence (AI), Cognitive Computing, etc.
5 general skills for Principal AI Engineer, Cloud Computing, Deep Learning, Machine Learning, etc.
9 soft skills for Principal AI Engineer, Innovation, Attention to Detail, Time Management, etc.
While the list totals 22 distinct skills, it's important to note that not all are required to be mastered to the same degree. Some skills may only need a basic understanding, whereas others demand a higher level of expertise.
For instance, as a Principal AI Engineer, he or she needs to be skilled in Innovation, be skilled in Attention to Detail, and be skilled in Time Management.

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