AI engineer salary calculator for New York City

Most salary calculators run on self-reported figures: whatever people typed into a form, whenever they typed it, for whatever job they said they had. This one runs on something better. Since November 2022, New York City has required employers to publish a good-faith salary range on any posting for a role performed in the city. Our NYC AI Hiring Index reads the job boards of 47 New York AI companies every morning, parses the range off each posting, and keeps the parsed figures after the posting disappears.

In the November 14, 2026 snapshot, 782 open roles were tagged to New York and 711 of them carried a usable range, a coverage rate of 91%. Ranges are cut by function and seniority and never blended across them, because an engineering median that includes sales roles is not a number anyone can use. Identical ranges within a company are counted once so boilerplate can’t set a median. On-target earnings are excluded, since folding commission into a base figure is how salary data becomes useless. Any cell with fewer than 8 observations is dropped rather than estimated, which is why some levels may be missing from the calculator on a given day.

The calculator anchors on the engineering function only. For each posting it takes the midpoint of the range, then reports the 25th percentile, the median, and the 75th percentile of those midpoints across every posting at the selected level. The table below is the same data, rendered plainly.

A posted range is a legal disclosure, not an offer. Employers post wide because the law lets them and because a wide band preserves room to hire across experience levels under one title. In practice, most offers land between the 40th and 60th percentile of the posted range. Almost nobody is hired at the top of it, and the candidates who get there usually walk in with a competing offer in hand. So when the calculator shows a median, read it as the realistic center of what a solid candidate is offered. Read the 75th percentile as the ceiling a strong candidate with leverage can reach, not a starting point.

One thing in the November 14, 2026 reading is worth naming: the senior median ($207,500, 43 ranges) is $7,500 above the mid-level median ($200,000, 62 ranges). That isn’t an error. “Senior” is a common title for production AI hires in New York, and companies advertise a senior role while hiring across a wide experience range, so the two posted bands overlap. The staff and principal median is $250,000, $42,500 above the senior one, and its 75th percentile is $265,000. If you have five or more years of production work and an offer that reads as senior, negotiate on level, not on title.

One more thing the data can’t show: these are base figures. The upside, whether options, restricted stock, or cash bonus, almost never appears in a posting. That is why the right-hand panel of the calculator is modeled rather than observed, and why Neuronify’s negotiation guide spends as much time on equity as on base.

Within engineering, the disciplines that earn a premium are not the fashionable ones. They are the ones where a bad hire is most expensive and hardest for a non-expert to detect in advance. Research and model training carries the largest uplift in the calculator, 12%, because the pool is small and the work is hard to fake. ML infrastructure and platform work, AI security, evaluation engineering, and agentic systems each carry 6 to 8%: these are the disciplines where unsupervised mistakes compound and where a buyer cannot tell from a resume whether the candidate has actually done it in production.

Generalist AI application work, which includes most of what gets posted as “AI engineer,” is the baseline. Production RAG and retrieval work sits just above it, because the skill is now common enough that the premium has compressed. The premiums here are smaller than the ones in Neuronify’s rate calculator for independents for a reason: a salaried specialist is priced against a band, while an independent specialist is priced against the cost of the problem.

The way to actually capture a premium is evidence, not keywords. Production systems you can talk through in detail, outcomes someone will vouch for, and the ability to explain what went wrong on the last one.

A basis point is one hundredth of one percent. A grant of 25 basis points is 0.25% of the company. Startups quote equity this way because the numbers stay legible: a senior engineer at a Series B company might see 10 to 35 basis points, a staff engineer 25 to 75, and the same roles at a seed-stage company several times that, because the company is worth a fraction as much. The calculator’s stage toggle applies those conventions and the valuation slider converts them into a dollar figure.

Treat that dollar figure with suspicion, in three specific ways. First, it is paper value at an assumed valuation, and private valuations are set by the last investor, not by a market. Second, options carry a strike price; what you eventually receive is the spread between the strike and the exit price, not the headline. Third, every subsequent funding round dilutes your stake, typically by 15 to 25% per round, and liquidation preferences mean investors are paid before you are in anything short of a strong exit. The annualized figure in the calculator divides the grant by four to match a standard four-year vest with a one-year cliff. It is a way to compare offers, not a forecast.

Restricted stock at public companies is a different instrument: worth face value on vest, usually quarterly, with annual refresh grants that matter more over time than the initial one. And in finance the upside is cash, paid as a discretionary bonus that at senior levels routinely equals base. When the calculator shows a bonus panel instead of an equity panel, that is why. The questions to ask about each structure are in Neuronify’s negotiation guide.

The summary panel includes a line most salary tools leave out: loaded cost. Payroll taxes, benefits, equipment, and software add 25 to 40% on top of base in the US, and the calculator applies a 1.3× multiplier, inside that range. At the posted medians in the November 14, 2026 reading that puts a senior AI engineer at about $270,000 a year and a staff or principal engineer at about $325,000, before equity, before a bonus, and before the search itself.

That math works when you have a durable, full-time-shaped problem and the management capacity to make a senior hire productive. It does not work as well for a build with a defined end, where an independent engineer or a small firm delivers the system without the permanent seat and the long search. Many mid-market teams sequence it deliberately: consultants ship the first version, then a cheaper, easier-to-hire engineer maintains and extends it.

Neuronify’s hiring guide covers the full-time path if that is the right one.