AI Salary Explorer
A quick, transparent estimate of total-compensation ranges for AI and software roles in 2026. Pick a role, level and company tier and it shows an indicative band, built from a public base rate and clearly-labelled tier and level multipliers rather than a black box. Calibrated so the anchors match reported figures — a senior big-tech AI engineer around the low-$200Ks, a frontier-lab senior in the high-six-figures. These are self-reported market ranges for orientation and negotiation prep, not an offer or advice — always verify live on a source like Levels.fyi.
The company tier is the biggest lever — total comp is equity-dominated at the top, so a frontier lab can pay multiples of a big-tech number for the same role. AI-specific roles carry a reported ~50%+ skills premium, encoded in their higher base rates.
Compensation for AI roles in 2026 spans a huge range, and the biggest driver is not the job title — it is the company tier and how much of the package is equity. This explorer is deliberately a transparent model rather than a scraped table: it takes a public base rate for each role at a senior big-tech level, multiplies by a level factor (mid, senior, staff, principal) and a tier factor (traditional enterprise, big tech, well-funded startup, frontier lab), and shows the result as a band. Because the math is visible, you can see exactly why a number is what it is, instead of trusting a black box.
The model is calibrated against reported anchors so it stays grounded: a senior big-tech AI engineer lands around the low-$200Ks in total compensation, matching commonly-cited averages, while a frontier-lab senior role lands in the high-six-figures, matching the reported medians for those labs. The role base rates encode the AI-skills premium — the reported ~50%+ wage advantage for AI-specific work — by paying AI/ML engineers, research engineers and applied scientists above a generalist software engineer, and the frontier-lab tier multiplier captures how fiercely those labs compete for scarce talent.
The honest framing matters as much as the numbers: these are indicative, self-reported market ranges for orientation, not an offer, a guarantee, or personalised advice. Real compensation depends on the specific company, location, level, equity terms and your negotiation — variables no general model captures. Use the band to sanity-check whether an offer is roughly in-range before you respond, then bring live, source-backed comparables for the exact role to the actual negotiation. It is a starting point for the conversation, not the last word.
How it works
- Indicative total-comp bands by role × level × company tier.
- Transparent: base rate × level multiplier × tier multiplier.
- Calibrated to reported anchors (big-tech, frontier-lab).
- Orientation and negotiation prep — not an offer or advice.
Frequently asked questions
Where do these numbers come from?
They are a transparent multiplier model, not scraped live data. A public base rate for each role (at a senior big-tech level) is scaled by a level multiplier and a company-tier multiplier, then shown as a band. The model is calibrated so its anchors line up with widely-reported figures — a senior big-tech AI engineer around the low-$200Ks in total comp, and frontier-lab senior roles in the high-six-figures. The point is orientation and a sanity-check, not a precise quote for your situation.
Why company tier matters so much
Because total compensation is dominated by equity at the top end, and equity scales enormously with the company. A traditional enterprise pays mostly cash; big tech layers on substantial stock; a well-funded startup trades cash for upside; and frontier AI labs, competing hard for scarce talent, push total comp to multiples of the big-tech number — which is why the tier multiplier is the biggest lever in the model. The same role and level can differ two- or three-fold across tiers.
Is there really an AI-skills pay premium?
Reported research has put the wage premium for AI-skilled roles at roughly 50% or more versus otherwise-similar roles without them. That premium shows up here as the higher base rates for AI-specific roles (AI/ML engineer, research engineer, applied scientist) relative to a generalist software engineer, and in how aggressively the frontier-lab tier scales. Treat it as a real but noisy signal, not a guaranteed raise — the premium varies by market, level and how core the AI work actually is.
Can I negotiate with these numbers?
Use them to calibrate, not to quote. The value of a band is knowing whether an offer is roughly in-range, below, or above market before you respond — that framing is most of negotiation. But bring live, source-backed data for the specific company and level to the actual conversation, because ranges move and your leverage comes from precise, verifiable comparables, not a general model. Pair this with the negotiation guide linked below.