Postings that carry the exact title AI engineer are a countable slice of the live catalogue: 640 right now, next to 652 machine learning engineer postings, 6,263 LLM postings, and 9 prompt engineer postings. The sections below put a salary, a share, and a tool ranking on each of those four labels, then list the live openings. Measured October 2026.
The number this article rests on: 640 live postings with AI engineer in the title, out of 7,564 across the four core AI titles and 168,899 tracked postings overall. Measured October 2026.
Titles are matched in the posting headline only, case-insensitively: "AI engineer", "machine learning engineer" or "ML engineer", "LLM", and "prompt". A posting that describes AI work without using one of these four labels is counted in the catalogue totals but in none of the four title slices, which is why the four counts add up to less than the full 168,899. Seniority, salary, and remote status for these slices are read the same way everywhere else on this site: from the posting text, never inferred.
The practical consequence is that searching the single phrase "AI engineer" misses most of the relevant openings. The 652 machine learning engineer postings alone outweigh the exact-title slice, and the 6,263 LLM postings describe substantially the same day-to-day work under a newer label. Candidates who watch all four labels see roughly 7,564 openings where single-label searchers see 640. The data jobs hub and the software engineering jobs hub hold most of these roles; the roles that build AI systems page isolates the ones where AI is the product rather than a tool.
How many AI engineer jobs are open right now?
640 live postings carry the exact title AI engineer, against 652 for machine learning engineer, 6,263 for LLM, and 9 for prompt engineer, for 7,564 titled openings combined. Title matching is headline-only and case-insensitive, so near variants like senior AI engineer count while descriptive phrases without the label do not. Measured October 2026.
The ranking between the four labels moves slowly: machine learning engineer remains the plurality title even as LLM postings grow from a smaller base, and prompt engineer stays the smallest of the four. None of the four counts includes postings that do AI work under other titles, so each is a floor for its slice rather than a ceiling on the underlying demand.
What do AI engineer postings pay?
Regarding listed pay, postings titled AI engineer show a median maximum of $251,104 on 160 USD ranges. Salary figures here are posted ranges in USD with both bounds stated; hourly rates are annualized and ambiguous amounts are excluded rather than guessed, which keeps small samples out of the medians. Measured October 2026.
The gap that matters most is not between the four titles but between postings that publish a range and the majority that do not: only 44,243 of 168,899 tracked postings carry a usable USD range. A title slice with fewer than ten such postings gets no median on this page, and the market-wide figure above is the fallback benchmark until its sample grows.
AI engineer vs machine learning engineer: which title dominates postings?
Machine learning engineer dominates by count at 652 live postings versus 640 for the exact AI engineer title, a ratio that has held across snapshots because enterprise postings standardized on the older label years ago. The LLM label, at 6,263, is the growth story of the four but still trails both incumbents in absolute count. Measured October 2026.
For candidates this means the two labels describe overlapping pipelines, not separate professions: the same employers, the same categories, and largely the same tool requirements appear under both. Watching only the newer AI engineer label filters out the larger, older pool, while watching only machine learning engineer misses the LLM-titled roles that skew toward applied language-model work.
Which tools do AI-titled postings name most often?
Across all tracked postings, the three most named tools are Python (10,338), Aws (6,301), and Excel (4,601), counted once per posting when the name appears in the text. A posting can name several tools, so these counts overlap rather than add up, and skills described without a product name are not counted here. Measured October 2026.
Tool counts describe what postings mention, not what gets a candidate hired: Python-adjacent ecosystems dominate the mentions because they dominate the posting text, while evaluation, orchestration, and deployment practices that matter on the job are described in prose the counter cannot see. Candidates should read these three names as the vocabulary of the listings, then verify the actual stack in each posting before applying.
The jobs right now
Live postings with AI engineer in the title, newest first, generated from the catalogue and not written by hand.
