The most difficult tech profiles to hire in 2026

Hiring technology has never been just about finding enough candidates. The real problem arises when a company needs specific experience in an area where demand is growing faster than the availability of professionals with truly applicable knowledge in production. In 2026, this pressure is particularly concentrated in Artificial Intelligence, cybersecurity, Cloud, Platform Engineering, and Data.

The World Economic Forum places AI and Big Data, Networks and Cybersecurity, and technological literacy among the skills with the highest expected growth by 2030. Among the tech roles experiencing the most expansion are Big Data Specialists, AI and Machine Learning Specialists, and Software and Applications Developers.

Data from the Linux Foundation reinforces the same pattern. Its 2026 State of Tech Talent Report identifies particularly relevant gaps in AI Engineering (47%), Cybersecurity & Compliance (40%), FinOps and Cost Optimization (36%), Platform Engineering (34%), and Cloud Computing (29%).

Talking about the most difficult tech profiles to hire in 2026 means identifying where demand growth, specialization, and a shortage of productive skills intersect.

1. AI engineers

The AI Engineer profile is likely one of the most pressured hiring roles currently. The growth of generative AI has led many companies to want to move from using tools like ChatGPT or Claude to integrating AI into real products and processes. This transition requires professionals who know how to build solutions, not just use tools.

This profile can work with LLMs, RAG systems, AI agents, model APIs, integrations with existing systems, process automation, response evaluation, and enterprise architectures. The difficulty is not simply in finding professionals who have tried AI tools but in finding profiles capable of bringing solutions to production, integrating them with existing systems, and managing security, costs, and quality. The Linux Foundation specifically points out that AI Engineering presents one of the largest gaps in technological capacity in 2026.

2. Machine learning engineers

The Machine Learning Engineer remains another complex profile to incorporate. Their work requires combining different disciplines: Machine Learning, Software Engineering, Data, Cloud, and MLOps. It is not enough to develop a model in a test environment; the professional must be able to train it, deploy it, monitor it, and maintain it as data and business requirements evolve.

Moreover, the World Economic Forum places AI and Machine Learning specialists among the fastest-growing roles by 2030. This combination of growth and specialization explains why Senior profiles can be particularly difficult to find. Companies need professionals who understand not only how to train a model but also how to integrate it into an existing software architecture.

3. Cybersecurity specialists

Cybersecurity remains one of the areas with the greatest skills shortages. However, there is an important difference compared to previous years: the problem does not seem to be solely the lack of people but the lack of specific competencies within existing teams.

The ISC2 study from 2025 shows that 59% of participants identified critical or significant skills needs within their cybersecurity teams, compared to 44% the previous year. Additionally, AI and Cloud Security appeared among the main technical shortages. Within this field, profiles such as Cloud Security Engineer, Security Engineer, SOC Analyst, DevSecOps Engineer, IAM Specialist, Application Security Engineer, and Pentester can be particularly difficult to fill. Each of these roles requires a specific combination of knowledge that is not always easily found in the market.

4. Cloud security engineers

Cloud Security deserves its own category. It is not simply "cybersecurity + AWS." The professional needs to simultaneously understand Cloud architecture, IAM, networking, encryption, logging, containers, compliance, and application security. This combination of domains makes the profile particularly scarce.

In the ISC2 study, Cloud Security was one of the most demanded skills, and hiring managers ranked it among their top technical priorities. A company looking for a Senior profile with real experience in AWS, Azure, or Google Cloud, along with advanced security experience, may find itself in a particularly competitive market, where offers are contested among multiple organizations.

5. Cloud engineers

Cloud remains one of the areas where companies need specialization. The difficulty arises because a modern Cloud Engineer may need to combine knowledge of AWS, Azure, or Google Cloud with Kubernetes, Terraform, networking, IAM, automation, observability, and cost optimization. This combination of skills makes the profile complex to find.

The Linux Foundation identifies Cloud Computing among the areas with significant skills gaps in both its 2025 and 2026 reports. Cloud adoption is already mature; the challenge now is finding professionals capable of operating complex architectures securely, efficiently, and scalably, and who also understand how to optimize costs in multi-provider environments.

6. Platform engineers

Platform Engineering is one of the profiles that has evolved the most recently. These professionals build internal platforms that allow developers to work on standardized environments without having to directly manage all the complexity of infrastructure. Their work has a direct impact on the productivity of the development team.

It may include knowledge of Kubernetes, Internal Developer Platforms, CI/CD, observability, Infrastructure as Code, service catalogs, and developer experience. The 2026 State of Tech Talent Report identifies Platform Engineering as one of the main technological skills gaps, with a 34%. Additionally, CNCF points out that Platform Engineering is changing how developers interact with Kubernetes and Cloud infrastructure.

7. DevOps engineers with Cloud Native experience

DevOps has been among the most sought-after profiles for years, but specialization has increased. It is no longer enough to know how to configure a pipeline. In certain environments, a DevOps Engineer may need knowledge of Kubernetes, Docker, Terraform, GitOps, CI/CD, Cloud, observability, and security. As Cloud Native architectures become mainstream, finding professionals with real experience managing these technologies in production becomes more important.

CNCF notes that Kubernetes has established itself as a central infrastructure for modern applications and AI workloads; 82% of surveyed container users reported using Kubernetes in production. This means that DevOps Engineers with Cloud Native experience are increasingly needed and, at the same time, harder to find.

8. Data engineers

Many companies want to implement AI, but first, they need to resolve their data issues. This is where the Data Engineer comes in. This profile builds data pipelines, ETL or ELT processes, data warehouses, data lakes, streaming systems, and integrations between different information sources. Their work is the foundation on which AI and analytics projects are built.

They can work with technologies such as Python, SQL, Spark, Kafka, Databricks, and Snowflake. The growth of AI and Big Data is indirectly increasing the importance of this engineering layer. The World Economic Forum precisely places AI and Big Data as the technological skill with the highest expected growth and Big Data Specialists among the roles with the most expansion.

9. Big data engineers

Not all companies need Big Data, but those that do require professionals with a particularly high level of specialization. A Big Data Engineer may have to work with distributed processing, Spark, Kafka, streaming, Databricks, Cloud, data lakes, and high-volume architectures. The combination of infrastructure, data engineering, and distributed architecture significantly reduces the pool of truly Senior candidates.

This profile can be especially difficult in projects that handle large volumes of data or real-time processing. The ability to design systems that process terabytes of information with reduced latencies is uncommon and requires years of experience in real production environments.

10. Specialized senior backend engineers

Not all hiring problems lie in emerging technologies. Software and Application Developers continue to rank among the fastest-growing tech roles in the World Economic Forum's projections. However, the difficulty increases when the company seeks Senior profiles with specific combinations: Java with Spring Boot, Kubernetes and AWS, or .NET with Azure, microservices, and distributed architecture, or Python with FastAPI, Data, and Cloud.

The problem is usually not finding someone who knows Java or Python but finding deep experience in the complete stack, architecture, and business context. Senior profiles who have worked on long-term projects, with distributed teams, and in high-demand environments are the hardest to incorporate.

Why are these profiles so difficult to hire?

There are several common factors that explain this difficulty. Technology evolves faster than experience: many tools reach enterprise adoption before there is a large number of professionals with several years of real experience. This is especially evident in AI, where the pace of change is dizzying.

Companies need increasingly specific combinations of skills. It is becoming less common to hire for an isolated technology, and combinations such as AI with Cloud and Backend, Security with Cloud, Data with Cloud and MLOps, or DevOps with Kubernetes and Security are sought. The more specific the combination, the smaller the available candidate pool. Additionally, real seniority makes a big difference: it is not the same to have used a technology as it is to have operated it under real load, made architectural decisions, and solved complex problems in production.

Should a company try to hire all these profiles internally?

Not necessarily. An organization may need technological capability without needing a new permanent position. A project may require a Cloud Security Engineer during a migration; a startup may need an ML Engineer to turn a prototype into production; a Backend team may temporarily require a Platform Engineer to develop an internal platform. In those scenarios, expanding the permanent staff may not be the only or most efficient alternative.

The ISC2 study itself reflects that organizations turn to outsourcing, third parties, and temporary professionals among the strategies used to cover skills gaps in cybersecurity. This trend is extending to other technological areas where talent shortages are particularly pronounced.

IT outsourcing for hard-to-find tech profiles

Through IT outsourcing, a company can incorporate one or more specialists to reinforce specific capabilities without committing to permanent hires. For example, an internal team composed of a CTO, Backend, and Frontend may temporarily need a Senior DevOps and a Cloud Security Engineer. Instead of starting two lengthy permanent hiring processes, these professionals can be brought in as an extension of the existing team.

This model allows access to specialized talent in record time, reducing the risks associated with lengthy selection processes and permanent commitments. It is especially useful when the need is temporary or when the local market does not offer the required profiles.

Team as a Service when the problem is not a single profile

At other times, the difficulty lies not in finding one person but in building a complete capability. An AI project may need an AI Architect, an AI Engineer, a Data Engineer, an MLOps Engineer, and a Backend Developer working in coordination. A Cloud platform may need a Platform Engineer, DevOps, Cloud Engineer, and Security working together.

Here, a Team as a Service model allows building the team around the objective, rather than approaching each position as an independent hiring process. This approach reduces friction, accelerates startup, and ensures that the profiles are aligned with the project's strategy.

How lateam works with specialized tech profiles

At lateam, we help companies incorporate specialized tech professionals through IT outsourcing and Team as a Service models. The search does not simply begin with a list of technologies. First, we analyze the problem, the tech stack, the level of responsibility required, the composition of the existing team, the expected duration of the project, and the business context.

From there, profiles can be identified in areas such as Artificial Intelligence, Machine Learning, Data, Cloud, DevOps, Cybersecurity, Backend, Infrastructure, and Design. The hiring difficulty is not resolved by presenting more candidates but by better defining what person the project really needs. This approach aligns with lateam's positioning: long-term relationships, technical criteria, and selection based on both capabilities and human fit.

Frequently asked questions

What are the most difficult tech profiles to hire in 2026?

The largest current gaps are particularly concentrated in AI Engineering, Cybersecurity, Cloud, Platform Engineering, and areas related to Data and Big Data. The specific difficulty varies by seniority, stack, and market.

Why are AI specialists so hard to find?

Because business demand is growing rapidly, and profiles capable of combining AI, software, data, and production operation are needed, not just experience using generative tools.

Is there still a shortage of professionals in cybersecurity?

Yes, although recent research from ISC2 increasingly emphasizes the lack of specific skills and not just the lack of headcount.

Which Cloud profiles present the greatest specialization?

Cloud Engineers, Cloud Security Engineers, Platform Engineers, SREs, and professionals with advanced experience in Kubernetes, Infrastructure as Code, and Cloud optimization often require complex combinations of knowledge.

Is it better to hire these profiles internally or outsource them?

It depends on whether the capability is strategic and permanent or responds to a specific need. Many companies combine internal teams with external specialists to cover specific skills.

Can complete teams be built instead of hiring profiles individually?

Yes. Through models like Team as a Service, different specialists can be grouped around a common technological objective.

Conclusion

The most difficult tech profiles to hire in 2026 share one characteristic: they are not difficult simply because there are few candidates, but because companies need increasingly specific combinations of experience. AI with Cloud, Cybersecurity with Cloud, Data with Machine Learning, DevOps with Platform Engineering, and Backend with distributed architecture.

The hiring challenge has evolved. It is no longer just about looking for a technology within a CV. It is about identifying what combination of skills, seniority, and experience the project really needs. When that capability is hard to find locally, expanding the talent market or incorporating specialists flexibly can become a more efficient alternative than keeping a vacancy open for months.

Access hard-to-find tech profiles

At lateam, we help companies incorporate specialized professionals through IT outsourcing and Team as a Service models, connecting organizations with tech talent from LATAM. From a single specialist to complete engineering teams, we can help you identify the capabilities your project needs. Tell us about your project and we will connect you with the talent you need in 48 hours.