Artificial intelligence is clobbering the workforce, and hundreds of thousands are about to lose their jobs, as new data from LinkedIn shows just how fast AI jobs are gaining traction. Its Jobs on the Rise 2026 report ranks the 25 most rapidly expanding positions in America, and AI-fueled roles are dominating high up that list — cutting through both tech and traditional sectors.
The takeaway is that employers are scrambling for people who can build, deploy, and operationalize AI — as well as leaders who can translate the technology into business outcomes. From model engineers to strategy consultants and data annotators, this increase crosses hands-on technical and advisory labor.
LinkedIn’s No. 1 Slot Goes to the AI Engineer Role
AI engineer meets machine learning engineer in the top spot on LinkedIn. These same experts are architecting models that help decide, automate, and solve complex problems — a practice increasingly central in product roadmaps and enterprise transformation.
Skills in demand include LangChain and Retrieval-Augmented Generation to build LLM applications, as well as PyTorch when developing a model. The greatest number of hires are at Technology and Internet, IT Services and Consulting, and Business Consulting. San Francisco, New York City, and Dallas are locations to watch.
Typical background is 3.7 years of prior experience; almost all applicants come from software engineering, data science, or full-stack backgrounds. Flexibility is there, but not everywhere: some 26 percent of roles are remote-only and another 27 percent hybrid. That blend indicates that employers want tight cycles among engineering, product, and users — while competing for talent far outside their backyard.
Strategic AI Roles Surge Across Sectors and Cities
Coming second on LinkedIn’s list is AI consultant and strategist. These experts aid organizations in use case assessment, pilot stand-up, and MLOps management while balancing risk with ROI. Product skills profile: Large Language Models, MLOps, and Computer Vision (bringing experiments to production-grade systems).
Hiring is focused in the same tech-forward realms, with jobs based in San Francisco, New York City, and Boston. It’s a senior lane: the median background is 8.2 years, typically from founder, software engineering, or product management roles. Work adaptations lean toward flexible, with 30% remote and 33% hybrid — which reflects the cross-functional nature of advisory work.
Behind the Models, Data Annotation Jobs Are Booming
And data annotator — sometimes “content analyst” — breaks into the top 10, a testament to a truth of AI development: good honey still requires bees. Reviewers tag and score text, images, audio, and code to help train and evaluate models according to strict criteria.
LinkedIn highlights SEO copywriting, content marketing, and content production as common skills that support the need for finer-grained instructions and domain-aware labeling — what we refer to as metaliteracy. The companies that are hiring run the gamut from tech platforms to staffing agencies and universities, while jobs cluster in Austin, New York City, and San Francisco. On average, an annotator has 3.5 years of experience, and many have a background as content manager, editor, or data analyst. About 27 percent of positions are remote, and 29 percent hybrid.
Research and Infrastructure Functions Grow
AI/ML researcher is at No. 5 on the list, suggesting companies and labs still want people to produce original model work in addition to applied engineering. In-demand skills are PyTorch, Deep Learning, and Computer Vision, with hiring being strong in Technology and Internet, Higher Education, and Research Services. The jobs are clustered around San Francisco, New York City, and Boston; the average years of experience is about three, with career tracks coming from data science, software engineering, or ML engineering. Roughly 16% of these jobs are remote and another 24% hybrid.
Further down at No. 17, data center technician exemplifies the physical spine of AI’s boom. These roles deploy and maintain servers, storage, networking, and power systems that support GPU-intensive workloads. Required skills are to manage data center infrastructure, operations, and cabling. Recruiting is focused in Washington, D.C., Atlanta, and Columbus, Ohio. Applicants typically come with 3.8 years of experience from IT support or data center operations. Just 3.6 percent of all jobs are work-from-home, and 32 percent are hybrid — touch-the-product work is the dominant model.
Collectively, the rankings indicate demand ranging from frontier research to applied productization, data quality, and the compute footprint that enables it all.
Methodology and What This Means for Job Seekers
LinkedIn analyzed millions of data points from members’ jobs between Jan. 1, 2023, and July 31, 2025, then ranked the roles by their growth rate while filtering for sustained momentum and a large enough number of hires. The list also highlights an increase in self-employment: founders and freelance consultants land high on the ranking, as well as jobs such as venture partner, business development executive, and quantitative researcher.
For candidates, the message is tactical. If you are technical, aim for tools and patterns employers name-check: PyTorch, LangChain, RAG, LLM fine-tuning, and MLOps. Ship small, concrete projects — an evaluation harness, a retrieval pipeline, or a safety/red teaming workflow — to show impact. For business-side talent, foster knowledge of model capabilities and limitations, governance, and change management to link engineering with operations.
The gravitational pull still runs to San Francisco, New York City, Boston, Austin, Dallas, Washington, D.C., Atlanta, and Columbus. But with a supply of roles material enough to offer remote or hybrid work, particularly in certain sectors (like engineering and strategy), remote workers elsewhere may actually have the advantage. The bigger takeaway from LinkedIn: AI skills are no longer niche; they are increasingly essential across the fastest-growing jobs in the U.S.
