Andela collected data from 47,101 technical job postings from Fortune 500 companies and 2,026 skill descriptions.
New research from global talent platform Andela has found that in a working landscape being transformed daily by AI, organisations are failing to update their job descriptions and titles in line with changes.
Andela’s ‘Emerging Skills Research’ collected data from 47,101 technical job postings from Fortune 500 companies and 2,026 skill descriptions.
A core finding of the research was the revelation that 53pc of AI job postings are asking for skills that don’t match the listed job title, highlighting a disconnect between organisations, recruiters and jobseekers.
“AI is changing tech workflows faster than ever and we need new ways to get ahead of those changes,” said Carrol Chang, Andela’s CEO.
“This groundbreaking research, based on our proprietary skills taxonomy updated for the AI world, provides a headlight, not a rear-view mirror.
“With it, companies will identify emerging roles and skills ahead of the market, enabling both enterprises and employees to be more strategic and successful.”
Rambling roles
Andela’s research found that among the roughly 1,832 postings targeting people with titles such as AI engineer and ML engineer, more than half of the required skills pulled from at least two different and established roles.
The report said: “For familiar titles like AI engineer, companies are seeking a different, unnamed role that includes skills such as LLM orchestration, autonomous agent and vector databases. Or, companies hire data scientists but then ask them to ship LLM agents.”
Reviewing job listings from Fortune 500 companies, Andela found that 23 ‘groups’ of skills kept appearing together, but without any official job title being attached. Eight of the groups appeared to suggest a brand new kind of job, 14 were found to be hybrids of old jobs with new skill expectations, and one was dropped due to a lack of confirmed data.
Two examples of ‘new jobs’ discovered are MLOps pipeline engineer, which combines parts of five existing job roles into one, and LLM application engineer, where someone builds apps using AI models that already exist, instead of building those models from scratch.
Andela found 6,758 job listings essentially asking for an LLM application engineer – they listed all the relevant skills, but the companies didn’t use that job title because it doesn’t officially exist yet. This shows companies need these skills faster than the job market has caught up with proper names for them, according to the research.
The report said: “The findings underscore the challenges companies face, driven by the unprecedented speed of change in the post-AI era, to accurately identify emerging skills, name them and attach them to job roles. Mismatches result in lost time, money and opportunity for both employer and employee.
“Job descriptions written for yesterday’s roles filter out the candidates companies actually need. Companies that fail to see emerging needs for human skills, especially as AI changes what it can do, will continually chase the wrong thing, and companies who hire today for yesterday’s roles will likely accrue ‘talent debt’ alongside technical debt.”
According to Cory Hymel, an author on the report and Andela’s head of research, gaps that widen the divide between what companies think they are hiring for and what the role truly requires are becoming structural liabilities.
As of now, there are a number of emerging tech roles as identified in the research, which include: MLOps pipeline engineer; LLM application engineer; FinOps reliability engineer; docs-as-code engineer; product front-end engineer; lakehouse analytics engineer, DevSecOps security engineer; and SecOps observability engineer.
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