Tech hiring in 2026 is not a rising tide. Indeed found that only 19% of tech job titles with meaningful posting volume were above their pre-pandemic level in early 20254. But inside that uneven market, demand for a small set of roles is climbing fast — and these are the roles where clients most often tell us they’re losing candidates to competitors.
1. AI and machine learning engineers
Companies are moving AI from pilots into production, and that takes engineers who can build, deploy and maintain LLM applications and agents — not only researchers. “Artificial intelligence engineer” ranked first on LinkedIn’s Jobs on the Rise list for the US in 20261, as it did in 20252. The World Economic Forum lists AI and machine learning specialists among the three fastest-growing jobs in percentage terms3. Demand for agentic-AI skills specifically rose from 0.06% of US postings in 2024 to 0.23% in 20255.
Most acute in AI companies · SaaS · banking and fintech · healthcare
2. Data engineers
AI projects more often stall on data than on models. Gartner found 63% of organizations either don’t have, or aren’t sure they have, the right data management practices for AI — and predicts organizations will abandon 60% of AI projects unsupported by AI-ready data through 20266. The World Economic Forum ranks big data specialists as the fastest-growing job in percentage terms3, and BLS projects data scientist employment to grow 35% from 2025 to 20357.
Most acute in retail (personalization, inventory) · banking · healthcare (clinical and claims data) · SaaS
3. Cybersecurity and AI security engineers
AI is both a new attack surface and the skill security teams most lack. ISC2’s 2024 study put the global cybersecurity workforce gap at 4.8 million, up 19% in a year8. In its 2025 study, 41% of respondents named AI as their top skill need, followed by cloud security at 36%9. BLS projects information security analyst employment to grow 21% from 2025 to 203510. Gartner warns that agentic AI is “creating new attack surfaces” as employees and developers adopt it11.
Most acute in banking · healthcare (PHI) · retail (payments) · AI companies
4. AI governance and model-risk specialists
As AI moves into credit, hiring and clinical decisions, someone has to document, test and defend it. In an IAPP survey, only 1.5% of organizations said they would not need additional AI governance staff in the next 12 months12. Gartner expects AI regulation to extend to 75% of the world’s economies by 203013. In the EU, rules for stand-alone high-risk AI systems now apply from December 2, 202714. US banks already apply the Federal Reserve’s SR 11-7 model-risk guidance, which calls for “effective challenge” of models by competent, independent staff15.
Most acute in banking · healthcare · AI companies selling into the EU · HR-tech SaaS
5. Cloud, platform and FinOps engineers
AI workloads add cost and complexity to cloud estates that were already hard to run. In Flexera’s 2026 survey, 73% of organizations said they lack the resources or expertise to manage their cloud environments effectively, and 85% named managing cloud spend as their top cloud challenge16. Cloud security is the second most-needed security skill in ISC2’s 2025 study9.
Most acute in SaaS · AI companies · retail (peak-season scale) · banking
6. Data center and GPU infrastructure technicians
The AI build-out runs on physical infrastructure. Data center technicians appear on LinkedIn’s 2026 Jobs on the Rise list1, and Indeed has noted postings for them “soared in demand”4. In Uptime Institute’s 2025 staffing survey, 37% of operators named hiring as one of their greatest challenges, with junior facilities staff in the shortest supply17.
Most acute in AI companies · hyperscale and colocation providers
7. Forward-deployed engineers (emerging)
AI vendors and large enterprises increasingly embed engineers with business teams to turn models into working workflows. One analysis of 1,000 postings found forward-deployed engineer jobs grew more than 1,100% year over year in 2025, with financial services and healthcare the most-named industries18. The sample is small, so treat this as a signal of an emerging role rather than a settled trend.
Most acute in AI companies and SaaS vendors selling into banking and healthcare
8. AI data and evaluation specialists
Generative AI output has to be labeled, checked and evaluated before customers see it. “Data annotators” ranked fourth on LinkedIn’s 2026 Jobs on the Rise list1. Gartner recommends building human-in-the-loop review into AI-supported processes11. Job titles here are still settling, but the work — reviewing and testing what models produce — is growing.
Most acute in AI companies · healthcare (clinical accuracy) · banking (model validation)
Where demand is cooling
For balance: routine coding is the clearest decline. BLS projects computer programmer employment to fall 7% from 2025 to 2035, noting that programming work “continues to be automated”19. Software QA analysts and testers are projected to grow 6%, slower than software developers at 10%20. Generalist and single-stack developer postings remain well below pre-pandemic levels4. The picture isn’t uniformly negative, though: the New York Fed found job postings show “little indication of a distinct AI-driven decline in labor demand” overall21.
How to staff for these roles
- Hire for production experience. For AI and data roles, ask what the candidate shipped and maintained — not only what they prototyped.
- Pair new roles with the people who own the risk. AI governance and security hires work best reporting alongside compliance, not only engineering.
- Use contract-to-hire for emerging titles. Forward-deployed and AI evaluation roles are still being defined; a contract start lets you shape the job first.
- Plan for scarcity. For security and AI engineering, build a shortlist before the requisition opens, not after.
