What 95 Generative AI Job Postings Reveal About Hiring Today

An analysis of 95 US-based Generative AI job postings pulled from Google Jobs reveals what these roles actually demand once buzzwords are stripped away. The core takeaway: most Generative AI jobs are applied engineering positions focused on building with existing models rather than training foundation models from scratch. The most notable finding is that RAG and agents have effectively merged into a single skill signal — 78% of postings mentioning agents also mention RAG. The combination of LLMs, Python, and RAG appears together in roughly a third of listings, making it the highest-leverage skill set to prioritize.

On tooling, LangChain dominates orchestration frameworks, OpenAI leads among model providers with Anthropic/Claude as a fast-growing second choice, and cloud preference follows AWS, then Azure, then GCP — with nearly 30% of postings requiring familiarity with more than one cloud platform. Among postings that disclosed compensation, the median pay midpoint sat around $187k, ranging from $121k to $274k.

The report also challenges common assumptions about where the jobs actually are: only 13% of postings come from recognizable Big Tech companies, while nearly half originate from lesser-known mid-market firms, consultancies, and contractors. Focusing exclusively on famous employers means competing for a small, crowded slice of the market. Roles requiring a US security clearance make up about 13% of postings and represent a comparatively low-competition path for those who qualify.