Exploring Artificial Intelligence Career Paths: Opportunities in 2025

A career in artificial intelligence offers enormous potential due to the rapid growth of the AI sector. Many organizations are racing to onboard qualified professionals and developers as industries shift toward AI, machine learning, and automation, driving an increasing demand for skilled staff. Given the technology’s emergent nature, many roles in the AI industry are still open to definition—or perhaps even yet to be invented. But one thing is clear: AI technology’s technical, ethical, and regulatory complexity calls for an equally diverse set of skills and responsibilities, from prompting and programming to research and ethical oversight. Here’s what you need to know about 13 of the most promising AI career paths in this burgeoning field, including critical skills, learning pathways, and earning potential.

TABLE OF CONTENTS
ToggleAI Careers: Job Titles, Descriptions, and SalariesAI ConsultantAI Prompt SpecialistAI ProgrammerAI DeveloperData ScientistAI Research ScientistMachine Learning EngineerDeep Learning EngineerNatural Language Processing (NLP) EngineerRobotics EngineerAI Product ManagerComputer Vision EngineerChief AI OfficerHow to Start a Career in Artificial IntelligenceThe Future of AI Career PathsFrequently Asked Questions (FAQs)The Bottom Line: AI Career Opportunities are Growing

AI Careers: Job Titles, Descriptions, and Salaries

The chart below provides a quick overview of the job titles, duties, and average annual salaries in today’s evolving AI sector. Note that salaries are based on industry averages in the U.S. from sources including Glassdoor, Salary.com, Indeed, and ZipRecruiter and may vary widely depending on a variety of factors.

Job TitleAverage Annual SalaryDescriptionAI Consultant$140,900Advises and supports businesses in implementing AI technologies and guiding integration to meet strategic goals.AI Prompt Specialist$95,500Develops prompts to guide generative AI models like ChatGPT.AI Programmer$143,000Programs algorithms to support AI-based applications, optimizing code for efficiency and functionality.AI Developers$129,300Designs and implements AI software and services, focusing on user-ready products and system robustness.Data Scientist$115,700Solves complex problems by extracting insights from data, often to inform AI model training.AI Research Scientist$117,700Researches new AI methods, tests algorithms, and contributes to AI advancements.Machine Learning Engineer$165,700Develops machine learning models and algorithms for AI applications, often supporting production environments.Deep Learning Engineer$127,500Builds deep learning models with layered neural networks, often for predictive analytics.NLP Engineer$197,700Develops NLP systems that understand and process human language, focusing on language-based AI solutions.Robotics Engineer$120,400Builds, tests, and maintains robotic systems using specialized hardware and software.AI Product Manager$155,100Guides the development of AI products, bridging technical and business requirements for market-ready solutions.Computer Vision Engineer$122,800Develops AI models to interpret visual data, focusing on object detection and image classification tasks.Chief AI Officer$257,000–$480,000Oversees AI strategy at the executive level, ensuring alignment with organizational goals across departments.

AI Consultant

Artificial intelligence consultants advise and support businesses and other organizations in implementing AI technologies. Their responsibilities range from steering implementation projects to ensuring AI software is compatible with an organization’s technical and strategic requirements. Given their role of guiding clients through AI adoption and integration, AI consultants are expected to understand AI in its entirety. This includes being technically knowledgeable about machine learning and deep learning and knowledgeable enough to evaluate AI solutions and recommend their comprehensive application within organizations.

Certification or Degree

Certified Artificial Intelligence Consultant (CAIC™) offered by USAII 

Certified Artificial Intelligence Practitioner (CAIP) offered by CertNexus

Skills

Computing and programming expertise

Knowledge of AI/deep learning tools frameworks

Data analysis and interpretation

Knowledge of AI ethics

Strategic and financial acumen

Project management

Cross-functional collaboration and stakeholder management

Salary

According to Glassdoor, the average salary for an AI consultant is $140,900 per year.

Career Advancement Opportunities

Experienced AI consultants often progress to managerial roles, overseeing teams of consultants, guiding client engagements, and providing strategic guidance on AI programs. Alternatively, they can specialize, becoming senior advisors who consult on high-level AI initiatives or offer their expertise across multiple industries.

Learn more about the AI certifications that can advance your career.

AI Prompt Specialist

Also known as prompt engineers, these specialists develop prompts for generative AI models, including applications like OpenAI’s ChatGPT and Midjourney. Prompt engineers create instructions (prompts) that guide AI tools and help them produce specific results. Prompt specialists must understand how these tools work and how best to communicate with them. Because of the wide use of generative AI, prompt specialists can work in industries from advertising to manufacturing.

Certification or Degree

Prompt Engineering for ChatGPT by Vanderbilt University

ChatGPT Prompt Engineering for Developers by OpenAI and DeepLearning.AI

The Complete Prompt Engineering for AI Bootcamp

ChatGPT Masterclass: The Guide to AI & Prompt Engineering – Udemy

Skills

Expertise in natural language processing (NLP)

Proficiency in developing relevant and engaging prompts for various AI applications

Linguistic proficiency

Creative and adaptable writing

Iterative testing and learning

Salary

According to Glassdoor, the average salary for an AI prompt specialist is $95,500 per year.

Career Advancement Opportunities

As prompt engineers gain experience and demonstrate proficiency in creating effective prompts for AI systems, they may advance to a senior or specialist role where they lead prompt generation projects, guide best practices, and mentor junior team members. They may also specialize further in specific applications of AI or work with cross-functional teams, such as UX design or data science, to adopt prompt strategies for different business contexts.

AI Programmer

A career as an AI programmer requires expertise in programming algorithms that underpin AI-based services, apps, and software. AI programmers are also responsible for developing and optimizing algorithms, training machines to produce human-like responses, and troubleshooting issues within AI solutions. AI programmers must be adept at writing production-ready code and proficient in programming languages like Python, Java, and C++. A strong understanding of AI and machine learning frameworks is essential, as is knowledge of AI concepts like data structures, model evaluation, and scalability considerations.

Certification or Degree

Maryville University’s online artificial intelligence certificate

AI Nanodegree by Udacity

Skills

Proficiency in languages such as Python, Java, C++, or R

Knowledge of machine learning algorithms, techniques, and frameworks such as TensorFlow, Keras, and Scikit-learn

Algorithm design and optimization

Strong understanding of AI and machine learning frameworks

Soft skills like problem-solving, task management, and communicating complex ideas clearly

Salary

AI programmers can expect to earn an average salary of around $143,000, though salaries can be higher for those with advanced degrees, specialized skills, and several years of experience.

Career Advancement Opportunities

AI programmers have several career advancement opportunities. As they gain experience and expertise, they typically move into more specialized or senior roles, such as senior developer, AI architect, AI consultant, product manager, program manager, or technical lead.

AI Developer

While their roles often overlap with programmers, AI developers typically design and implement the AI-based software and services that end up in the hands of end users. Their role involves integrating AI models into functional software and ensuring that the AI aspects perform as intended. For this reason, AI developers usually work alongside AI programmers and data engineers to make AI systems more robust and efficient.

Certification or Degree

IBM AI Developer Professional Certificate on Coursera

Global Tech Council’s Certified Artificial Intelligence (AI) Developer certification

Certified AI Developer by Blockchain Council

Skills

Proficiency in programming languages such as Python, Java, or C++

Knowledge of machine learning algorithms and techniques

Experience working with big data technologies like Hadoop, Spark, or Apache Flink

Strong problem-solving skills and analytical thinking

Experience with cloud platforms such as AWS, Azure, or Google Cloud

Familiarity with software development best practices and version control systems like Git

Salary

According to ZipRecruiter, the average salary for an AI developer is $129,300 per year.

Career Advancement Opportunities

AI developers have a wealth of career opportunities. They can progress into senior developer positions or transition into roles such as AI architect, researcher, or AI consultant, among other specializations.

Data Scientist

A key responsibility of data scientists is solving complex problems by extracting insights from data. Data scientists perform duties including building models using programming languages, finding patterns in data sets, communicating insights to stakeholders, and consulting with organizations on how to best use their data. Data science plays a crucial role in AI, transforming raw data into structured insights used to train more sophisticated AI models.

Certification or Degree

IBM Data Science Professional Certificate on Coursera

The Data Science Council of America’s (DASCA) Senior Data Scientist (SDS) certification program

Azure Data Scientist Associate certification from Microsoft

Skills

Strong knowledge of programming languages such as Python, R, or SQL

Proficiency in data analysis and statistical tools

Familiarity with machine learning algorithms and techniques

Ability to work with large datasets and databases

Attention to detail and accuracy in data analysis

Salary

According to Indeed, the average salary for a data scientist is $115,700 per year.

Career Advancement Opportunities

At a more senior level, data scientists may have the opportunity to become chief data officer responsible for the organization’s data strategy and governance, ensuring that data-driven insights are used to drive business decisions.

AI Research Scientist

A career as an AI research scientist involves exploring the use of AI to uncover new opportunities—most of which are yet to be defined. Researchers also build algorithms and perform experiments to test new AI methods. Research scientists must be highly inquisitive and creative. They must also have a firm grasp of complex subjects such as statistics, data analytics, machine learning, and natural language processing.

Certification or Degree

Certified Research Scientist (CRS) offered by the American Statistical Association (ASA)

Certified AI Research Scientist (CAIRS) program offered by American Institute of Business and Management

Skills

Strong background in computer science, mathematics, and statistics

Deep understanding of machine learning algorithms and neural networks

Proficiency in programming languages such as Python, Java, or C++

Ability to analyze data and draw meaningful insights from data analytics

Experience with AI research projects and publications

Continuous learning about the latest developments in the field of AI

Salary

According to Glassdoor, the estimated pay for an AI research scientist is $117,700 per year.

Career Advancement Opportunities

There’s a growing need for professionals who can address AI’s ethical considerations and policy implications. As such, AI research scientists can transition into roles focused on AI ethics, responsible AI development, and policymaking related to AI technologies. Alternatively, they can transition into a career in academia, teaching AI courses, and conducting research at universities or research institutions.

Machine Learning Engineer

The machine learning (ML) engineer is foundational in developing AI programs, applications, and software. Machine learning engineers work to design the models and algorithms that make AI work. Designing these models requires the ML engineer to organize data, test models, program AI models using languages like Python, and perform production-level tasks to support ML development.

Certification or Degree

Professional Machine Learning Engineer by Google

Andrew Ng’s Machine Learning Specialization on Coursera

IBM Machine Learning Professional Certificate on Coursera

AWS Certified Machine Learning – Specialty on Coursera

Skills

Strong knowledge of machine learning algorithms and techniques

Proficiency in programming languages such as Python, R, or Java

Familiarity with data manipulation and analysis tools like NumPy, Pandas, and Scikit-learn

Experience with data visualization libraries like Matplotlib and Seaborn

Understanding of statistics and probability theory

Knowledge of deep learning frameworks such as TensorFlow or PyTorch

Ability to work with big data technologies like Hadoop, Spark, or SQL

Salary

According to Indeed, the average salary for a machine learning engineer is $165,700 per year.

Career Advancement Opportunities

ML engineers can specialize further in their fields, becoming senior engineers or progressing to technical lead roles. They may also transition toward machine learning research, focusing on developing new algorithms, techniques, and technologies within the field of ML. This role requires a strong background in computer science and mathematics.

Read more: Best Machine Learning Certifications

Deep Learning Engineer

Deep learning is a branch of machine learning that uses multi-layered neural networks to analyze large datasets and identify complex patterns that inform its outputs. Deep learning powers image and speech recognition technology, allowing models to learn directly from data instead of relying on explicit programming for each task. Deep learning engineers use this process to build highly intelligent AI models, most often to support predictive analytics. These engineers must be machine learning, neural networking, data science, and programming experts.

Certification or Degree

IABAC’s Certified Deep Learning Expert Certification (CDLE – AI3060)

Certified Deep Learning Associate by Skillfloor

Certified Deep Learning Expert Course offered by Datamites Global Training Institute

Skills

Proficiency in programming languages such as Python, C++, or Java

Strong foundation in mathematics, especially linear algebra, calculus, and statistics

Understanding of machine learning algorithms and techniques

Familiarity with deep learning frameworks such as TensorFlow, PyTorch, or Keras

Experience with data preprocessing, feature engineering, and model evaluation

Knowledge of neural network architectures and how to design and optimize them

Salary

According to Glassdoor, the average salary for a deep learning software engineer is $127,500 per year.

Career Advancement Opportunities

With experience and proven expertise in deep learning, professionals can advance into leadership positions such as technical lead, team manager, and project manager, overseeing and guiding teams of AI/ML engineers.

Natural Language Processing (NLP) Engineer

Natural language processing, or NLP, refers to a computer’s ability to understand human language. NLP is a major force behind chatbots and popular AI tools like ChatGPT. A career as an NLP engineer requires deep expertise in programming AI models and systems that can understand human language. While NLP engineers must be skilled in programming and machine learning, a solid understanding of language structure and semantics is also important for building effective language-based models.

Certification or Degree

Natural Language Processing Specialization on Coursera (offered by DeepLearning.AI)

Natural Language Processing (NLP) with Python for Machine Learning on Udemy

Natural Language Processing in TensorFlow on Coursera (offered by Deeplearning.AI)

Natural Language Processing Nanodegree by Udacity

Skills

Proficiency in programming languages such as Python, Java, or C++

Strong knowledge of natural language processing techniques and algorithms

Familiarity with data preprocessing and text processing tools

Good understanding of language structure and semantics

Salary

According to Talent.com, the average NLP engineer salary is $197,700 annually. 

Career Advancement Opportunities

An NLP engineer can specialize further in their field by progressing to more senior technical fields. This might include becoming an NLP architect, where they’d typically be responsible for designing and implementing an organization’s overall architecture of NLP systems. Alternatively, an NLP engineer might transition into a role as an NLP researcher or consultant.

Robotics Engineer

Robotics engineers use specialist hardware and software to build robotic systems, including testing, troubleshooting, and maintenance. The skills required to be a robotics engineer are a unique—and complex—mix. Beyond AI, programming, and mathematics knowledge, robotics engineers typically need hands-on mechanical skills and a strong understanding of electronics, sensor technology, and control systems.

Certification or Degree

Robotics Engineering & Applications offered by L&T EduTech on Coursera

Certified Robotic Engineer Courses by SMEC

Robotics Engineering Certificate Program by Bradley University

Skills

Strong understanding of robotics principles and systems

Proficiency in programming languages such as C++, Python, and MATLAB

Knowledge of electronics and electrical systems

Ability to design, build, and troubleshoot robotics systems

Strong analytical and mathematical skills

Understanding of mechanical engineering principles

Familiarity with robotic sensors and actuators

Salary

According to Salary.com, the average salary for a robotics engineer is $120,400 per year.

Career Advancement Opportunities 

Robotics engineers can advance their careers by specializing in specific areas of robotics, such as autonomous navigation, computer vision, or industrial automation. They may also choose to move into leadership roles, such as project manager or robotics team lead, overseeing larger development projects and guiding teams, or pursue roles in research and development.

AI Product Manager

AI product managers bridge the gap between technical and business teams, guiding the development of AI tools so they fit real-world use cases and business objectives. They’re usually the professionals who set the vision and roadmap for AI products, meaning the role typically requires technical know-how and strong business acumen.

Certification or Degree

IBM AI Product Manager Professional Certificate on Coursera

AI Product Management by Duke University

Artificial Intelligence for Product Certification (AIPC) by Product School

Skills

Product strategy and roadmap planning

Understanding of AI technologies and applications

Knowledge of agile software development practices, continuous integration, and continuous deployment (CI/CD)

Knowledge of DevOps practices

Ability to translate technical capabilities into user-friendly features

Project management and cross-functional collaboration skills

Interpersonal and communication skills

Salary

According to Glassdoor, the average salary for an AI product manager is $155,100 per year.

Career Advancement Opportunities

AI product managers can move into senior or executive product management roles, where they might lead entire AI portfolios or departments or oversee broader AI strategy within an organization. Alternatively, they may explore opportunities in AI consulting, where they can advise organizations on AI product development and strategy.

Computer Vision Engineer

Computer vision engineers build AI models that enable computers to interpret visual data like images and videos. They also program algorithms for tasks such as object detection, facial recognition, and image classification, which are essential in industries like automotive (for self-driving cars), healthcare (for medical imaging), and security (for surveillance systems and access controls).

Certification or Degree

MathWorks Computer Vision Engineer Professional Certificate on Coursera

Computer Vision Bootcamp on Udacity

Visual Computing Graduate Certificate by Stanford Online

Computer Vision Certification by Carnegie Mellon University

Skills

Proficiency in computer vision frameworks like OpenCV and MatLab and deep learning libraries like TensorFlow and PyTorch

Knowledge of image processing techniques and algorithms

Programming expertise, particularly in Python and C++

Experience with data preprocessing and augmentation

Familiarity with hardware acceleration and GPU programming

Salary

According to Glassdoor, the average salary for a computer vision engineer is $122,800 per year.

Career Advancement Opportunities

Computer vision engineers can advance into research roles, technical lead positions, or managerial roles, overseeing AI applications in specific sectors like autonomous vehicles or surveillance technology.

Chief AI Officer

Chief AI officers (CAIOs) are the senior executives responsible for shaping and overseeing an organization’s AI strategy. They ensure that AI initiatives align with business goals and drive the development and integration of AI technologies across departments and teams. CAIOs often oversee cross-functional teams, meaning they need strong leadership skills, an understanding of business strategy, and sound technical expertise. In many organizations, the responsibilities of a CAIO might fall under the roles of chief technology officer (CTO), head of data science, or VP of AI/ML.

Certification or Degree

Executive Certificate in AI and Business Strategy by MIT Sloan

AI in Business Strategy by Harvard Online

Skills

Strategic planning and business acumen

Advanced knowledge of AI technologies and applications

Leadership and cross-functional collaboration

Data governance and ethics

Salary

According to Glassdoor, the average salary for a chief AI officer varies widely, from $257,000 to over $480,000 annually. 

Career Advancement Opportunities

As C-suite executives, chief AI officers are typically close to the top of the organizational hierarchy. They may advance their careers by moving into broader C-suite roles, such as CTO, where they can guide AI and other technical portfolios across the organization. Alternatively, they may move into advisory or board positions to provide strategic guidance on AI and digital transformation to various organizations.

How to Start a Career in Artificial Intelligence

If you’re considering a career in AI, a few essential steps will help you get started: selecting a career path, gaining relevant skills, building a portfolio, and seeking out entry-level roles.

Choose an AI Career Path

AI encompasses various specialties, so take the time to explore the roles that align with your skills and interests. Consider your strengths: if you have a strong mathematical background, data science or machine learning engineering roles may be a good fit. For those interested in AI applications within physical systems, robotics could be an exciting path. Read plenty of job descriptions and talk to industry professionals to understand what each path entails.

Gain Relevant Education and Skills

Once you have a path in mind, start building the necessary knowledge. AI roles often require proficiency in programming (especially in Python), statistics, and specialized fields like machine learning or data science. You might pursue an AI-focused degree, certification, or online courses. Many online platforms offer courses from introductory to advanced levels, covering specific skills like neural networks or natural language processing. Internships or apprenticeships can also provide real-world experience and are valuable additions to your training.

Build a Portfolio of AI Projects

An AI portfolio helps demonstrate your practical skills to potential employers. Start by working on small, relevant projects in your area of interest. For example, if you’re interested in machine learning, create and train a model using a dataset; if you’re focused on NLP, perhaps try building a basic chatbot or sentiment analysis tool. Documenting your work on GitHub or a personal website to showcase your projects will ensure you have a record of your skills for prospective future employers.

Network and Seek Entry-Level Roles

Once you’ve built a portfolio, begin looking for entry-level roles in AI. Focus on junior positions. Networking can be a key part of your job search, so connect with AI professionals on LinkedIn, attend industry meetups or conferences, and get involved in online communities. Starting a career in AI takes time, so keep updating your skills, stay curious, and be open to learning new areas as the field evolves.

The Future of AI Career Paths

The artificial intelligence industry is experiencing a profound boom. To put its pace of growth in context, the market size was $95.6 billion in 2021, and by 2030, it’s forecast to reach $1.8 trillion, growing at a CAGR of 36.6 percent. This growth will drive AI companies and other organizations to hire additional staff. According to the Bureau of Labor Statistics, computer and information technology jobs will increase by 15 percent between now and 2031. This is much faster than the average growth of all other occupations.

Job opportunities range from those specific to AI to those specific to data and machine learning. Due to the nature of AI and its complexities, there are virtually endless career paths to choose from.

Frequently Asked Questions (FAQs)

Is AI a Good Career? AI is a highly promising and lucrative career field with a growing demand for skilled professionals. With advancements in technology and the increasing integration of AI in various industries, pursuing a career in AI can lead to numerous opportunities for growth and development. How do I break into a career in AI? To land an entry-level AI position, you typically need skills in programming languages such as Python, R, Java, or C++, and knowledge of data structures, algorithms, and machine learning concepts. Strong analytical and problem-solving abilities and a solid understanding of statistics are also important for success in AI roles. Which Industries Hire AI Professionals? AI professionals are in demand across a wide range of industries, including—but not limited to—healthcare, finance, retail, manufacturing, automotive, and technology. Is AI hard to learn? Learning AI can be challenging, especially if you don’t have a programming, mathematics, or computer science background. It covers several complex topics like machine learning and statistics, all requiring a good grasp of math and coding (Python is especially popular). That said, it’s by no means impenetrable. With dedication and the right resources—like beginner-friendly courses or YouTube tutorials—AI is learnable. Start with the basics and build from there. Consistent practice and hands-on projects help you grow your skills and confidence in AI—or any other field, for that matter.

The Bottom Line: AI Career Opportunities are Growing

As the AI industry continues to grow, so will the opportunities for a highly successful career as an AI professional. While AI uses software and hardware to perform its highly technical work, humans are still the masterminds behind it. If you’re considering a new career path in tech, a career in AI might be an exceptionally rewarding fit.

Explore our extensive list of the 150 top AI companies focus on this dynamic technology and reshaping how it is used.
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