GenAI demand is best read through vacancy evidence, role context, and the technologies used alongside it. ApplyDjinn separates core and required usage from supporting mentions so candidates can distinguish hands-on ownership from general stack exposure. Current hiring evidence includes EPAM, Amazon, Google. Leading observed locations include United States, India, Remote.
2,116 live roles98 hiring companies29% remote-friendly
Vacancy evidence map
Where GenAI carries hiring weight
Each segment represents roles where GenAI was parsed at that evidence tier. This keeps a required production skill separate from contextual stack language.
169 Core759 Required923 Supporting265 Optional
928core + required44% of mentions
21.6roles per company98 employers
Market interpretation
What GenAI demand means in practice
GenAI can represent different work depending on the role family and delivery environment. The live evidence map on this page shows whether employers treat it as a primary capability, a required implementation skill, supporting context, or an optional advantage. Companion demand such as AI, Cloud, Machine Learning, Scalability helps explain the actual systems and responsibilities behind the keyword.
A credible GenAI application should connect the skill to a concrete system, decision, and result. State what you built, configured, migrated, secured, tested, or operated; name the scale and constraints; and explain the outcome. This gives hiring teams stronger evidence than a standalone skill badge or an undifferentiated list of tools.
Data and AIApplied engineeringPlatform deliveryAnalytics and operations
Reading the market
Signals to look for
Read GenAI together with AI, Cloud, Machine Learning, Scalability; combinations reveal the likely workload and ownership boundary.
Core and required mentions deserve more weight than incidental text in a company or product description.
Role title, seniority, location, and adjacent skills determine whether prior experience transfers directly or needs a focused ramp-up.
It counts fresh vacancies where GenAI was found in title, requirements, responsibilities, or stack evidence. The tier breakdown separates central requirements from supporting and optional mentions.
How should GenAI appear on a CV?
Tie it to a specific project or production responsibility, the surrounding stack, the constraint you handled, and an outcome. Match the depth of the claim to the evidence shown in the target vacancy.
How GenAI appears in job requirements
Inferred from the title and requirement wording in 2116 active roles; each role is counted once. Read the methodology.
Posting evidence, not a company-wide stack claim
Main / core
8%(169)
Required
36%(759)
Supporting / context
44%(923)
Nice-to-have
13%(265)
Skills mentioned with GenAI
A shared posting does not always require both skills. Explicit alternatives are counted separately.