10 top AI jobs in 2026

Top AI job skills

Demand for AI specialists continues to grow as organizations move beyond experimentation and work to operationalize AI at scale. Unlike general roles that may simply use AI-powered tools, AI specialist positions require deep technical expertise in building, deploying, securing and governing AI systems.

At the same time, the skills required for these roles are evolving rapidly. According to PwC's 2025 Global AI Jobs Barometer analysis, skills in jobs exposed to AI are changing 66% faster than in less AI-exposed roles. While the report examines AI's effect across the entire workforce -- not specifically AI specialist jobs -- it highlights the pace at which AI-driven skill requirements are changing.

From a technical perspective, proficiency in core programming languages such as Python, Java and R remains foundational. However, employers increasingly prioritize experience that goes beyond model development. Hands-on knowledge of machine learning (ML) model training, deployment, monitoring and machine learning operations (MLOps) has become important as AI systems move into production environments.

Organizations also value expertise in areas such as prompt engineering, data pipeline management and human-AI interaction design, especially as AI systems are embedded into customer-facing applications. Security, privacy and responsible AI practices are now integral parts of many AI roles, reflecting growing regulatory and governance requirements.

In addition to technical depth, AI specialists must work closely with business leaders, product teams and domain experts to translate AI capabilities into measurable outcomes. As a result, soft skills -- including communication, collaboration and critical thinking -- remain important differentiators in AI-focused roles.

Success in AI specialist jobs typically requires a combination of the following skills:

• Strong proficiency in AI programming languages and frameworks.
• Practical experience with model development, deployment and operations.
• An understanding of data management, security and AI governance.
• The ability to adapt as AI technologies and skill requirements evolve.
• Effective communication and cross-functional collaboration skills.

This mix of skills reflects the growing maturity of AI and the increasing demand for professionals who can move AI from concept to production in 2026.

Top industries embracing AI

Some industries are embracing AI faster than others. These include the following:

• Technology. Tech firms of all types are adding AI to their products to enhance their use and make them simpler and more user-friendly. Hyperscalers, such as Google, Amazon and Microsoft, are all actively hiring AI specialists to build services.
• Finance. The finance industry is making broad use of AI with simple tasks, such as automation, and more advanced uses, including improving risk management and making better investment recommendations and decisions.
• Healthcare. The healthcare industry is also rapidly embracing AI at all levels. On the low end, AI is being used for automation to avoid human error and for tasks such as billing and record management. On the high end, AI is being widely touted for early detection of serious illnesses, such as cancer, because AI can spot signs that humans might miss.
• Retail. The retail industry is making wide use of AI for operational efficiency. AI can be used for areas such as inventory management, loss prevention, trend spotting, more personal shopping experiences and fraud prevention by finding suspicious spending patterns or transactions.
• Manufacturing. The manufacturing industry is embracing AI for operational efficiency. AI can provide early detection of potential equipment failure and help machinery run efficiently.
• Cybersecurity. The cybersecurity market is embracing AI to monitor threats around the clock and to avoid human error. AI applications can be programmed to detect unusual activity quickly for swift action.

10 top AI jobs

AI jobs are changing at a fast pace, just like technology. In 2026, specialists are more sought after than generalists. Deep knowledge of one aspect of AI is more valuable than shallow knowledge across many areas.

Here are some of the top AI jobs to check out, in alphabetical order. Job titles may vary by organization, but these represent the most commonly used titles. Salaries listed reflect base pay estimates as reported by Indeed, LinkedIn and Glassdoor, and do not include bonuses, equity or other forms of compensation.

1. AI ethics officer

Ethical use of data used in generating models is a top concern in 2026. Dedicated specialists are needed to ensure responsible AI development and deployment. Companies might also look to add an AI ethics committee made up of employees with various experiences and specialties, including lawyers, engineers, ethicists, public representatives and business strategists.

An AI ethics specialist helps develop ethical guidelines and policies for AI projects and complete ethical reviews of these projects. They might report any findings to the AI ethics committee. Skills needed for this position include critical thinking, effective communication and familiarity with AI frameworks and regulations.

Expected salary: $120,000-$180,000 annually.

2. AI for healthcare specialist

If ever there was an industry that needed a bridge between the technological side and the professional side, it is healthcare. Technology can help doctors and patients alike in many ways, but it is also one of the most sensitive fields when it comes to data privacy.

AI offers several opportunities for helping the medical profession, such as diagnosing diseases and identifying the best treatment plans for patients with critical medical decisions. Another example of AI in healthcare is the use of AI-powered robotics in the operating room to assist surgical procedures.

AI jobs in healthcare require a deep understanding of medical conditions and terminology, as well as AI expertise.

Expected salary: $150,000-$250,000 annually.

3. AI product manager

An AI product manager is similar to other product managers. Both jobs act as team leaders to develop and launch a product. In this case, it is an AI product, but it's not much different from any other product in terms of leading teams, scheduling and meeting milestones.

The technological demands of this job are a little higher than for most product manager positions. AI product managers need to know what goes into making an AI application, including the hardware, programming languages, data sets and algorithms, so that they can make it available to their team. Creating an AI app is not the same as creating a web app. There are differences in the structure of the app and the development process.

Expected salary: $113,000-$152,000 annually.

 4. AI research scientist

AI research scientists are computer scientists who study and develop new AI algorithms and techniques. They develop and test new AI models, collaborate with other researchers, publish research papers and speak at conferences. Programming is only a small portion of what a research scientist does.

The tech industry is extremely open to self-taught and non-formally trained programmers, but there is an exception when it comes to AI research scientists. They need to have a strong understanding of computer science, mathematics and statistics. Typically, they need graduate degrees.

Expected salary: $123,000-$177,000 annually.

5. AI solutions architect

An AI solutions architect is responsible for designing end-to-end AI systems that align technical capabilities with business requirements. Rather than building individual models, this role focuses on how AI components fit into broader enterprise architectures, including data pipelines, cloud infrastructure, security controls and governance frameworks.

AI solutions architects work with CIOs, engineering teams and business leaders to evaluate use cases, select appropriate AI technologies and design systems that are scalable, secure and compliant. They often play a key role in moving AI initiatives from pilot projects into production by ensuring systems can be integrated with existing enterprise platforms.

This position typically requires a strong background in software architecture, cloud computing and data engineering, along with a working understanding of ML and GenAI systems. Familiarity with AI governance, risk management and cost optimization is increasingly important as AI deployments grow in size and complexity.

Expected salary: $139,000-$200,000 annually.

6. Computer vision engineer

A computer vision engineer is a developer who specializes in writing programs that use visual input sensors, algorithms and systems. These systems, such as self-driving and self-parking cars and facial recognition, see the world around them and act accordingly.

Computer vision engineers use languages such as C++ and Python, along with visual sensors, such as Mobileye from Intel. Examples of use cases include object detection, image segmentation, facial recognition, gesture recognition and scenery understanding.

Expected salary: $96,000-$250,000 annually.

7. Cybersecurity analyst with AI expertise

AI has found a home in cybersecurity, particularly in intrusion detection. However, threat actors also use AI. This is a field where specialists are needed who are both fluent in cybersecurity and in the skill sets to use AI to combat issues such as ransomware and other intrusions.

These analysts develop and deploy AI-driven tools to monitor network activity, detect unusual patterns and respond rapidly to potential threats. They also work to anticipate and defend against AI-powered attacks. Key skills include deep knowledge of cybersecurity frameworks, proficiency in AI and ML applications for threat detection and strong programming abilities -- especially in Python. Analytical thinking and incident response capabilities are also important.

Expected salary: $120,000-$200,000 annually.

8. Data scientist

A data scientist is a technology professional who collects, analyzes and interprets data to solve problems and drive decision-making within the organization. They are not necessarily programmers, although many do write their own applications. Mostly, they use data mining, big data and analytical tools.

Their use of business insights derived from data enables businesses to improve sales and operations; make better decisions; and develop new products, services and policies. They use predictive modeling to forecast future events, such as customer churn, and data visualization to display research results visually. Some also use ML to build models to automate these tasks.

Expected salary: $94,000-$146,000 annually.

9. Machine learning engineer

An ML engineer designs, builds and deploys ML models that power AI applications in production environments. While data scientists often focus on analysis and experimentation, ML engineers focus on turning models into reliable, scalable systems that can operate in real-world conditions.

ML engineers work closely with data scientists, software engineers and product teams to select appropriate algorithms, train models on large data sets, optimize performance and integrate models into applications. Their work often includes managing model pipelines, monitoring performance in production and retraining models as data changes.

This role typically requires strong programming skills, particularly in Python, along with experience using ML frameworks such as TensorFlow or PyTorch. Knowledge of cloud platforms, containerization and MLOps practices is increasingly important as organizations deploy AI at scale.

Expected salary: $102,000-$152,000 annually.

10. Robotics engineer

A robotics engineer is a developer who designs, develops and tests software for running and operating robots. Robotics has advanced significantly in recent years. Examples include automated home cleaners, robotic nurses and precision cancer surgery equipment. Robotics engineers might also use AI and ML to boost a robotic system's performance.

As a result, robotics engineers typically design software that receives little to no human input, instead relying on sensory input. Therefore, a robotics engineer needs to debug the software and the hardware to make sure everything is functioning as it should.

Robotics engineers typically have degrees in engineering, such as electrical, electronic or mechanical engineering.

Expected salary: $87,000-$140,000 annually.

Andy Patrizio is a technology journalist with almost 30 years' experience covering Silicon Valley who has worked for a variety of publications -- on staff or as a freelancer -- including Network World, InfoWorld, Business Insider, Ars Technica and InformationWeek.