ResearchApril 24, 202618 min read

New Types of Jobs Created by AI in 2026

A detailed, source-backed look at the new types of jobs created by AI in 2026, including AI artists, prompt engineers, LLM optimization specialists, AI security researchers, AI video creators, AI content strategists, and other emerging roles.

SQ Team

Market Research

AI Careers

New Types of Jobs Created by AI in 2026

A lot of the conversation around AI and work still starts with the wrong question. People ask which jobs AI will replace. That question matters, but it hides another one that is now just as important: which new jobs is AI creating?

By April 2026, the answer is no longer theoretical. New AI-native roles are already showing up on official career pages across Europe and in global remote hiring. Some are highly technical. Some sit inside marketing, design, or brand teams. Some are not fully standardised yet, which is exactly what makes them interesting. They are early indicators of where work is going next.

You can already see this in live listings for roles like AI Artist, Prompt Engineer, AI Video Creator, AI Optimization Specialist, LLM Optimization Specialist, AI Security Researcher, and AI Content Strategist. You can also see it in adjacent roles that did not exist in the same form a few years ago, such as AI Trainer, Evaluation Engineer, and Forward Deployed AI Engineer.

This matters for employers building new teams, but it matters just as much for people exploring engineering jobs, data science roles, design jobs, marketing jobs, product roles, and operations work. AI is not only creating a narrow class of machine learning roles. It is creating new hybrids across the wider economy.

And the macro data backs that up. On January 7, 2025, the World Economic Forum’s Future of Jobs Report 2025 said technological change is expected to create 170 million jobs and displace 92 million by 2030, for a net gain of 78 million roles. It also listed AI and machine learning specialists among the fastest-growing jobs. On October 28, 2025, the European Commission’s report on Shaping and strengthening European AI talent said AI talent in the EU more than doubled between 2016 and 2023 and now represents 0.41% of the EU workforce.

That does not mean every new AI job has a clean title or a settled career ladder. In fact, the opposite is true. Many of the most interesting roles sit between old categories. That is why looking at live job ads is so useful: they show where the market is actually spending money, not just which ideas sound good on a conference stage.

Quick Answer: What New Jobs Is AI Creating?

The clearest pattern in 2026 is that AI is creating role families rather than one neat list of job titles. The new roles usually emerge where AI changes a workflow enough that someone now has to design, steer, optimise, secure, or scale it.

Emerging job type	What the role usually does	Where it is showing up
AI Artist	Uses generative tools to create production-ready visuals, concept art, assets, and creative systems	Creative studios, gaming, advertising, entertainment, content production
AI Optimization Specialist / LLM Optimization Specialist	Helps brands and websites become more discoverable and accurately represented in LLM-based search and AI answer engines	SEO teams, content teams, growth teams, brand visibility platforms
Prompt Engineer	Designs, tests, versions, and improves prompts and LLM workflows for production use cases	Healthcare, gaming, customer support, enterprise AI platforms
AI Security Researcher	Studies misuse, attack paths, model transparency, red teaming, and AI-specific security risk	Government labs, frontier AI safety teams, security startups
AI Video Content Creator / Video Prompt Engineer	Builds AI-assisted video pipelines for ads, social content, cinematic production, or branded storytelling	Media, entertainment, growth marketing, creator tools, content studios
AI Content Strategist / AI Brand Voice Specialist	Uses AI systems to scale content, preserve brand voice, and shape how companies are discovered in AI-first channels	B2B SaaS, agencies, growth teams, AI-native brands
AI Trainer / AI Evaluator	Reviews AI outputs, improves model behavior, writes evaluation scenarios, and teaches systems domain reasoning	AI labs, freelance talent platforms, evaluation teams
Forward Deployed AI Engineer / AI Workflow Builder	Implements AI systems directly in customer environments and turns model capabilities into production workflows	Enterprise AI vendors, applied AI teams, solution engineering groups

These are role families, not rigid categories. In real job ads, titles often vary even when the underlying work is very similar.

That is the core takeaway. AI is not just generating more AI engineers. It is creating new work wherever model capabilities change what teams can produce, how quickly they can produce it, and what new risk or coordination problems appear as a result.

Why AI Is Creating New Jobs Instead of Only Replacing Old Ones

Technologies that change workflows often create new coordination work around themselves. That is what AI is doing now.

A useful way to think about it is this. Every time AI makes a task faster, cheaper, or easier, it also creates new needs somewhere else. Someone has to test the outputs. Someone has to define the tone of voice. Someone has to optimise how a company appears inside AI search. Someone has to secure model behavior. Someone has to turn a rough model capability into a repeatable business workflow. Someone has to combine taste and prompting inside creative production. Those new needs become new jobs.

PwC’s 2025 AI Jobs Barometer helps explain why this is happening. It says AI-exposed jobs are seeing skills change 66% faster than less exposed jobs, and workers with AI skills now command a 56% wage premium. In other words, AI is not only affecting which jobs exist. It is speeding up the creation of new skill combinations inside those jobs.

That is why many AI-created jobs look like hybrids. The market is not always inventing an entirely new profession from zero. More often, it is taking an existing discipline like design, security, content, search, or operations and layering AI-specific responsibilities on top until a new role family appears.

1. AI Artists

One of the clearest examples of AI creating a genuinely new role family is the rise of AI artists. This is not just a designer who happens to use Midjourney once in a while. In the strongest job listings, AI artists are expected to understand visual storytelling, prompt systems, asset pipelines, model fine-tuning, output consistency, and post-production quality.

A good example in Europe is BrainRocket’s AI Artist role in Valencia, Spain. The listing asks for expertise with Stable Diffusion frameworks, ControlNet modules, LoRA training, inpainting and outpainting, end-to-end AI art pipelines, and prompt engineering. This is already much closer to a specialised production role than to casual image generation.

The broader creative market is moving in the same direction. Wonder Studios’ AI Artist role focuses on creating AI-generated assets for campaigns, pitches, and productions, while OpusClip’s AI Artist role explicitly combines prompting, visual taste, and system-building for video. These are not just experiments. They are paid jobs with specific expectations.

What makes AI artists interesting is that they sit at the intersection of design, content production, and software-assisted creativity. The job exists because AI creates huge amounts of visual possibility, but still requires a human to guide style, narrative, consistency, and final quality.

2. AI Optimization Specialist (AIO) / LLM Optimization Specialist

This is one of the newest and fastest-emerging job families in the article. The title is still unstable. Some companies call it GEO, for generative engine optimization. Some say LLM optimization. Some frame it as AI search strategy or AI visibility. But the underlying work is becoming very clear.

These specialists help companies appear correctly and competitively inside AI-driven discovery systems like ChatGPT, Perplexity, Gemini, and Google AI Overviews. That means they work on machine-readable content structure, citations, entity clarity, discoverability, content architecture, and how brand information gets interpreted by large language models.

Europe already has solid proof that this is a real role family. Enpal’s SEO & LLM Marketing Intern role in Milan is explicitly about visibility across AI-based systems like ChatGPT, Gemini, and Perplexity. Malt’s SEO/GEO Manager role in Paris frames the work around AI and LLM ecosystems. Lodgify’s Senior Technical SEO/GEO Specialist role in Barcelona goes even further, focusing on how pages are parsed, summarised, and cited by LLMs and AI search systems.

This matters because it shows AI is creating new jobs even inside marketing and growth teams. Traditional SEO did not disappear. But AI-based search changed discovery enough that new specialists are now needed to manage visibility in those systems.

3. Prompt Engineer

Prompt engineer may be the most famous new AI job title, but the real market version is more serious than the internet stereotype. Employers are not paying people just to write clever prompts. They are hiring people who can treat prompts as part of a production system.

That means prompt engineers often work on prompt versioning, evaluation, fallback logic, multi-step workflows, reliability, guardrails, and domain-specific output quality. In practice, the role sits somewhere between product, software engineering, experimentation, and language design.

You can see that clearly in European job ads. Nabla’s Prompt Engineer role in Paris supports clinical AI workflows. Ubisoft’s Prompt Engineer role in Paris connects prompt engineering to gaming experiences and collaboration across AI, design, and QA teams. 10x Team’s remote EU and UK Prompt Engineer - AI Trainer role shows another variation, where prompt expertise is used to improve the reasoning quality of AI systems.

So yes, prompt engineering is a real job. But in 2026 it is better understood as an applied systems role than as a narrow prompt-writing niche. That is one reason many strong prompt engineers come from engineering, data science, or domain-heavy product environments rather than from copywriting alone.

4. AI Security Researcher

As AI systems become more capable, networked, and autonomous, they create new security work. That is why AI security researcher has become a meaningful job family instead of a small academic niche.

These roles can focus on misuse, red teaming, model transparency, evaluation, adversarial behavior, agent permissions, or how AI systems interact with sensitive environments. In other words, AI creates new attack surfaces and governance problems, so it also creates jobs dedicated to understanding and reducing those risks.

Europe already has visible demand here. The UK government’s AI Security Institute has roles such as Research Engineer or Research Scientist - Red Team (Misuse), Model Transparency, and other frontier-risk research posts. On the private side, Prelude’s Senior Security Researcher (AI) focuses on adversarial tradecraft and generative AI systems.

This is a good example of how AI creates jobs through side effects. The more AI gets deployed, the more somebody has to secure it, test it, challenge it, and understand how it might fail. That is new work, and it is likely to keep growing.

5. AI Video Content Creator / Video Prompt Engineer

AI video is one of the clearest places where a new creative profession is taking shape in real time. These roles usually combine prompting, visual sequencing, narrative structure, editing taste, model knowledge, and production workflow design.

The strongest version of the job is not just someone who can make a flashy clip. It is someone who can repeatedly produce usable, on-brand, high-performing video content with AI-assisted pipelines.

There is already concrete proof of this in European listings. Luni’s AI Video Creator role in Bordeaux is one example. Sporty’s AI Video Specialist role in Madrid explicitly frames the work around AI-driven video storytelling. HOLYWATER’s AI Video Creator role in Kyiv shows the same pattern in AI-native entertainment products.

What is happening here is important. AI is not only speeding up existing video workflows. It is creating a new layer of specialists who know how to combine models, prompts, editing, motion, style consistency, and brand requirements into a real content engine. That places these roles somewhere between design, marketing, and creative operations.

6. AI Content Strategist / AI Brand Voice Specialist

Another emerging AI job family sits inside content, narrative, and brand systems. These roles are appearing because AI increases content volume and speed, but also creates new problems: brand drift, inconsistent tone, poor factuality, weak discoverability, and messy coordination between human teams and AI tools.

That is where AI content strategists and AI brand voice specialists come in. Their job is not simply to write more content faster. Their job is to create systems so content stays structured, discoverable, distinctive, and consistent even when AI becomes part of production.

A clear example is Encord’s AI Content Strategist role in London, which focuses on how AI systems and search engines process and surface information. Another good signal is CloudWalk’s Brand Creative Copywriter – AI Driven role, which explicitly connects AI tools with scalable narratives, messaging frameworks, and brand voice systems. And from the model-improvement side, 10x Team’s Brand Specialist - AI Trainer role in Belgium shows that branding expertise itself is now being used to improve AI systems.

This is one of the most underrated areas where AI is creating work. Many companies assume AI will simply compress marketing headcount. What actually seems more likely is that stronger brand, content, and editorial operators who know how to control AI-assisted systems will become more valuable.

7. AI Trainer / AI Evaluator

This role family deserves more attention because it captures something important about the current phase of AI. Models still need human judgment. In fact, the more they spread into specialized work, the more they need expert humans to review outputs, create evaluation scenarios, test edge cases, and make sure generated answers behave like the real world.

That is why AI trainer and evaluator roles are multiplying, often in surprisingly domain-specific forms. 10x Team is hiring AI Specialist - AI Trainers in Poland, Principal Engineer - AI Trainers in France, Brand Specialists - AI Trainers in Belgium, and many other domain-specific trainer roles across the EU and UK.

That tells us AI is creating jobs not only for AI builders, but also for people who can teach, judge, and stress-test AI inside professional domains. This is especially important because it opens new pathways for experienced professionals who are not classic software engineers. Domain expertise itself becomes part of the AI labor market.

8. Forward Deployed AI Engineer / AI Workflow Builder

Another powerful new role is the person who turns AI into working business systems inside real customer environments. These jobs usually sit at the intersection of technical delivery, consulting, workflow design, and product adaptation.

A strong example in Europe is Mistral’s Applied AI, Technical Lead, Forward Deployed AI Engineer - EMEA role, based across Paris, Munich, London, and Amsterdam. Palantir’s Forward Deployed AI Engineer role in London describes the job as owning end-to-end workflows and taking high-stakes AI projects to production.

These roles exist because many companies do not need another abstract AI prototype. They need someone who can connect the model to the business, the tools, the customer process, the data, and the actual operational constraints. That is a very different kind of value, and it is why applied AI delivery roles are becoming one of the most important AI-created job families.

What These New AI Jobs Have in Common

Even though the titles look different, most of these roles share the same pattern. They are not pure AI jobs in the narrow sense. They are hybrid jobs.

AI Artist = visual storytelling plus generative tooling plus production taste.
AIO or LLM Optimization Specialist = SEO plus technical content structure plus AI search understanding.
Prompt Engineer = language design plus product thinking plus evaluation discipline.
AI Security Researcher = security research plus model behavior plus adversarial reasoning.
AI Video Creator = prompting plus editing plus narrative sequencing plus brand consistency.
AI Content Strategist = content systems plus brand voice plus discoverability across AI channels.
AI Trainer = domain expertise plus evaluation plus structured feedback for model improvement.
Forward Deployed AI Engineer = engineering plus workflow design plus customer implementation.

That hybrid structure is probably the most important insight in the whole article. AI is not just rewarding people who start from zero and learn one tool. It is often rewarding people who already have one strong discipline and then layer AI fluency on top of it.

What This Means for Employers

For employers, the lesson is straightforward. If AI is creating new roles inside your company, do not assume the right hire will look like a standard machine learning candidate.

Write the role around the workflow, not the hype. Say what the person will actually own.
Look for discipline-plus-AI combinations rather than AI-only generalists.
Decide whether the role is creative, technical, evaluative, strategic, or delivery-heavy before opening the search.
Treat new AI roles as cross-functional from day one. Most of them sit between teams.
Expect the best candidates to care about systems, quality, and repeatability, not just experimentation.

This is exactly why structured hiring matters. If you are building AI-first teams and need help defining role scorecards across engineering, marketing, design, product, or operations, SearchQualify’s company hiring page and recruitment support page are the clearest internal next steps.

What This Means for Job Seekers

For job seekers, this is good news if you approach it the right way. You do not always need to become a frontier AI researcher to benefit from the jobs AI is creating.

Often the smarter path is to start from the discipline you already know, then ask how AI is changing that discipline’s workflow. If you are in design, learn AI asset pipelines and consistency systems. If you are in marketing, learn AI discovery and content architecture. If you are in security, learn model misuse and AI risk. If you are in product or operations, learn where AI changes delivery, feedback loops, and system design.

If your current background is...	A strong AI-adjacent move could be...	Why it works
Designer or art director	AI Artist or AI Video Creator	You already have visual judgment. AI adds scale, variation, and system-building.
SEO or growth marketer	AIO / GEO / LLM Optimization Specialist	Search is shifting into AI-mediated discovery.
Writer, editor, or strategist	AI Content Strategist or AI Brand Voice Specialist	Brand systems now need AI-aware structure and governance.
Engineer or ML practitioner	Prompt Engineer, AI/LLM Engineer, or Forward Deployed AI Engineer	You can connect models to production systems and business workflows.
Security researcher	AI Security Researcher or AI Red Teamer	AI introduces new attack surfaces and model-behavior risks.
Domain expert in law, operations, brand, healthcare, or finance	AI Trainer or AI Evaluator	Labs and AI vendors increasingly need real-world experts to teach and test systems.

This is not a rigid career map. It is a practical way to think about how existing expertise can compound with AI rather than compete with it.

If you want to browse how those role families connect to current opportunities, start with the jobs by location page and then scan role clusters across engineering, data science, design, marketing, and product.

FAQ: Is AI Really Creating New Jobs, or Just Renaming Old Ones?

It is doing both. Some AI roles are clearly old disciplines with new tools layered on top. Others are new enough that the workflow itself did not really exist in the same form before, like GEO and LLM optimization, AI trainer work, or forward-deployed AI implementation. In practice, the difference matters less than whether the role solves a new problem that companies are now willing to pay for.

FAQ: Are AI-Created Jobs Only for Engineers?

No. That is one of the clearest themes in current listings. AI is creating jobs in creative production, branding, content systems, search visibility, evaluation, and workflow design as well as in engineering and research.

FAQ: Which of These New AI Jobs Are Growing Fastest?

Prompt engineering, AI content strategy, LLM and GEO optimization, AI video creation, and applied AI delivery roles are among the fastest-moving role families right now because they sit close to immediate business value. Security and evaluation roles are also becoming more important as AI systems get more powerful and more widely deployed.

FAQ: Which New AI Jobs Are Showing Up in Europe?

Europe already shows live demand for AI artists in Spain, prompt engineers in France, GEO and LLM optimization specialists in Italy, France, and Spain, AI video specialists in Spain and Ukraine, and AI safety or security roles in the United Kingdom.

FAQ: What Skills Matter Most Across These AI-Created Jobs?

The shared pattern is not one magic AI skill. It is the combination of domain expertise, AI tool fluency, experimentation, evaluation, communication, and systems thinking. The people who stand out are usually the ones who can make AI outputs useful, not just produce them.

Sources

The cleanest way to read the market in 2026 is this: AI is not only absorbing work. It is creating new work around itself. The people and companies that do best will usually be the ones who notice those new roles early, name them clearly, and build the right skill combinations around them.

Next up

How AI is impacting the job market in Europe