AI and infrastructure roles dominate the IT-related positions on LinkedIn’s latest Jobs on the Rise report, which ranks the fastest-growing roles in the U.S. over the past three years.
The 2026 list shows sustained demand for technical talent supporting AI development, deployment, and operations, alongside data center and quantitative roles tied to infrastructure and analytics.
AI engineers, also referred to as machine learning engineers, rank as the fastest-growing role overall. These professionals design and implement AI models used for tasks such as prediction and decision-making.
According to LinkedIn, the most common skills for AI engineers include LangChain, retrieval-augmented generation (RAG), and PyTorch. The role is most prevalent in technology, IT services, and business consulting, with the highest concentration of jobs in San Francisco, New York City, and Dallas.
Closely related are AI consultants and strategists, who focus on helping organizations plan and implement AI initiatives. Their work centers on aligning AI technologies with business goals. Common skills include large language models, machine learning operations (MLOps), and computer vision.
These roles are concentrated in the technology and consulting sectors, with hiring strongest in San Francisco, New York City, and Boston. Professionals entering these positions often come from software engineering, product management, or founder backgrounds.
Ali Gohar, chief human resources officer at Software Finder, says companies now value not only theoretical knowledge about AI but also the ability to implement it.
"The most in-demand skills that employers are prioritizing include hands-on programming in Python, familiarity with modern machine learning libraries such as PyTorch and TensorFlow, and the skills required for deploying and managing models in a production environment," he explains.
In addition, MLOps skills such as model versioning, monitoring, cost optimization, and governance are now seen as minimum requirements rather than differentiators in the case of AI-related jobs.
"For an AI consultant, it’s a combination of these requirements and the skill to scope out problems and determine what level of AI should be utilized for a particular problem and effectively communicate trade-offs," Gohar says.
AI and machine learning researchers also appear prominently on the list. These roles involve designing and testing new models and algorithms to advance AI systems.
The most cited skills include PyTorch, deep learning, and computer vision. AI/ML researchers are commonly employed in technology companies, higher education, and research services.
The report noted hiring is concentrated in major technology hubs, including San Francisco, New York City, and Boston, with many transitioning from data science or machine learning engineering roles.
Supporting AI development pipelines, data annotators, sometimes called content analysts, play a key role in preparing datasets used to train models. Their work involves labeling and reviewing data according to detailed guidelines.
The most common skills reported for this role include SEO copywriting, content marketing, and content production. Data annotators are frequently employed in technology, staffing, and higher education sectors, with jobs concentrated in Austin, New York City, and San Francisco.
Volen Vulkov, co-founder at Enhancv, points out tech titles are getting more and more generalized.
"In reality, an AI engineer means anything from heavy API consumption to even business solution consulting around bots," he says. "Therefore, personal branding and CPI advocacy are at the center of IT career breakthroughs."
He adds the rise in independent consultants, founders, and hybrid technical-strategy roles signals that traditional IT job stability is increasingly unreliable, while independence offers a new form of long-term security.
Vulkov says independents are building "portable" career assets in the background to empower independence from any traditional IT job’s "career capital."
"They place higher value on growing their own reputations, validating their brand, and creating solutions, case studies, and knowledge pathways that generate inbound work," he explains.
Data Center Technicians in Demand
Beyond AI development, the report highlights continued demand for data center technicians, who install, maintain, and troubleshoot servers and related hardware to ensure reliable operations.
Core skills include data center infrastructure, data center operations, and cabling. The role is most common in IT services and technology companies, with hiring strongest in Washington, D.C., Atlanta, and Columbus, Ohio.
Related to large-scale infrastructure projects, commissioning managers are responsible for testing and validating complex systems, including data centers, before they become operational.
Key skills include electrical testing, piping and instrumentation diagrams, and equipment testing. These roles are concentrated in engineering services and IT consulting, with hiring centered in Houston, Washington, D.C., and Dallas.
The report also includes quantitative researchers and analysts, who develop mathematical and statistical models to support investment and risk decisions. Common skills include algorithmic trading, statistical research, and backtesting. These roles span capital markets, technology, and research services, with the highest demand in New York City, Chicago, and Boston.
Gohar says infrastructure and operations jobs—including cloud engineers, site reliability engineers, and platform engineers—are still very in demand, as the complexity on the backend has increased with the advent of AI.
He explains the nature of the applications being developed with the help of AI are compute-intensive, costly, and prone to unavailability.
"It makes sense that employers are looking for people with expertise in making them run well, inexpensively, and reliably," Gohar says. "These are all infrastructure and operations roles that are very foundational; you can’t scale an AI business without these teams."
Prepping for an AI Future
Vulkov says given the "washing out" of tech titles with consulting and strategic roles (or so-called hybrid roles), an IT career cannot resolve itself to a list of projects in a traditional resume.
"Narrative and business-centric storytelling is a game-changer," he says. "Since the value of tech solutions today is all about business impact, this is what we urge IT applicants to do to their projects, prompt them to think about them narratively and map them on their resumes."
He encourages applicants to consider questions including: How did this chatbot redesign improve first-contact resolution? What did your work around model evaluation improve or reduce in existing workflows?
Gohar says traditionally defined IT boundaries are being eroded at a basic level because of the growing need for AI.
"Application programming is no longer the domain of software engineers because now they need to get involved in data pipelines, experimentation, and AI," he notes.
The tasks of infrastructure engineers themselves are undergoing a transformation, with the need for cloud-native infrastructure that supports GPUs, automation, and scaling.
Even data annotation engineers' tasks are becoming niche, with a growing need for domain knowledge, data quality, and ethics on the part of the hiring organization.
"From an HR viewpoint, there is a lack of linearity in career paths because of AI, and every IT skill is being pressed into a new shape," Gohar says.