Quick summary
Trump's executive order told the government to swap "AI" for "Super Intelligence." Here's who's actually hiring under that name, what they pay, and how to search for the job without chasing a word.
On September 29, 2026, Trump signed an executive order telling every federal agency to stop saying "artificial intelligence" and start saying "super intelligence." Within days, people were searching "super intelligence jobs" as if a brand new hiring category had opened overnight. It hasn't.
What's real is that a handful of frontier labs, Meta Superintelligence Labs, Safe Superintelligence Inc., and Microsoft's MAI Superintelligence Team, already built "superintelligence" into their name and mission, some of them more than a year before the government caught up with the vocabulary.
This guide separates the branding from the actual hiring: who's really posting roles, what they pay, and how an ordinary developer should search and position themselves, instead of chasing a word. For the broader market these roles sit inside, the AI engineer jobs guide is still where most of the actual hiring volume is.
1. The AI-to-SI Rename Is a Branding Order, Not a Jobs Program
A word swap, not new law
The executive order is called "Inaugurating the Era of Super Intelligence," and it's narrower than the headlines make it sound. It tells every executive branch department and agency to use "Super Intelligence" and "SI" instead of "Artificial Intelligence" and "AI" in official correspondence, public communications, and policy documents going forward.
It does not rewrite existing law, regulations, contracts, or grants, and it defines "Super Intelligence" as covering the exact same technologies already defined as artificial intelligence under 15 U.S.C. Section 9401(3). By November 28, 2026, the president's science and technology advisor has to propose actual legislative language for a formal definition.
Until that happens, this is a word swap inside government paperwork, not a new category of work.
An optics event, not a jobs program
Trump signed the order the same day he hosted a "Super Intelligence Luncheon" at the White House, where six tech leaders (Elon Musk, Jensen Huang, Sundar Pichai, Mark Zuckerberg, Dario Amodei, and OpenAI's Greg Brockman) signed a separate voluntary "White House Accord on Super Intelligence" committing to internal safety controls and outside oversight.
None of that creates jobs either. It's optics timed to a hiring reality that already existed: Meta renamed its AI division Meta Superintelligence Labs back in a 2025 reorg, more than a year before the government picked up the word.
The rename validated a label three companies were already using. It didn't invent new hiring.
2. Who's Actually Hiring for Super Intelligence Roles
Strip away the branding and three real employers are hiring under the "superintelligence" name right now, each with a very different hiring style.
The rename validated a label three companies were already using.
Meta Superintelligence Labs
Meta Superintelligence Labs (MSL) posts real, open roles on metacareers.com. Search "Meta Superintelligence Labs" there and you'll find listings across research, engineering, and content roles.
| MSL posting | Location | Posted base pay |
|---|---|---|
| AI Research Scientist, Product and Applied Research | Menlo Park | $219,000–$301,000 plus bonus and equity |
| AI Research Engineer, Media (multimodal foundation model training) | Sunnyvale or New York | $154,003–$217,000 |
| Content Engineer | Menlo Park | Roughly $162,000–$227,000 |
You'll also find an AI Research Scientist on the FAIR Foundations evaluations team, building the benchmarks that decide which capabilities get built next.
Those are posted base-salary ranges required under pay transparency law, not total compensation. MSL total comp runs far higher once bonus and equity are added, which the super intelligence engineer salary breakdown covers in detail.
Safe Superintelligence Inc.
Safe Superintelligence Inc. (SSI), founded by ex-OpenAI chief scientist Ilya Sutskever along with Daniel Gross and Daniel Levy, hires almost nothing like a normal company. It posts through a single Ashby job board and openings appear sporadically, sometimes dropping to zero listed positions for months at a time.
There's no internship program, and the company leans on direct outreach to researchers it already wants rather than public postings. SSI hit a $30 billion valuation in a March 2025 round led by Greenoaks Capital, six times its $5 billion valuation from six months earlier, on a company that wasn't generating revenue.
If you're waiting for an SSI job alert to fire, you'll likely wait a long time. This is a company you get noticed by, not one you apply your way into.
Microsoft's MAI Superintelligence Team
Microsoft's MAI Superintelligence Team formed in November 2025 under Mustafa Suleyman, who calls the goal "Humanist Superintelligence," AI that works in service of people rather than racing toward some abstract finish line.
The team includes Microsoft AI chief scientist Karen Simonyan, and by Microsoft Build 2026, it had shipped seven in-house frontier models spanning reasoning, code generation, image generation, and voice, Microsoft's biggest first-party AI release yet.
Suleyman has said the team is actively expanding and hiring researchers with "fundamental research capabilities."
Three real labs now use "superintelligence" as their brand, and all three hire by reputation as much as by resume. The free Rockstar Engineer Blueprint is a 5-day course from John Sonmez on getting known in your industry, so the recruiters at labs like these already know your name before you apply.
Get the Free Course3. What These Labs Actually Look For
The research track
Read the actual postings and two very different bars show up.
The research-scientist seats, the ones titled AI Research Scientist on evaluations, robotics, or FAIR teams, want a published research track record: a PhD or equivalent industry research output, hands-on experience with LLM post-training, and the ability to design the evaluations that decide what a frontier model ships next.
These are the hardest seats to get and the smallest in number.
The applied-engineering track
The research-engineer and applied seats are a different story. The AI Research Engineer role on MSL's Media team wants someone who can contribute to training multimodal foundation models and build data curation pipelines at scale, which is software engineering with machine learning fluency, not a publication list.
A Content Engineer role is closer still to product engineering, shaping how AI product experiences actually behave.
If you're a strong engineer without a research pedigree, these applied and engineering-flavored roles are the real entry point into a lab like MSL, not the research-scientist titles that dominate the headlines.
4. How Realistic Is This for a Normal Developer
The market most developers ignore
Here's the part nobody selling "super intelligence jobs" courses wants to say out loud. The combined headcount across MSL, SSI, and Microsoft's superintelligence team is small, likely in the hundreds to low thousands worldwide.
The broader AI engineer job market, the one covered in the AI engineer jobs guide, has tens of thousands of open roles at companies like Capital One, Salesforce, Microsoft outside MAI, and JPMorgan that need people who can ship AI features, not invent new model architectures.
Treating a frontier lab seat as the only real "AI job" worth having is how developers talk themselves out of a market that's actually hiring.
What the pay numbers actually show
Even Meta's own leadership pushes back on the mythology. Meta CTO Andrew Bosworth told employees the nine-figure offers went to a very small number of people in senior leadership roles, not to the rank and file.
Levels.fyi data puts Meta's E7 engineers at an average of about $1.54 million a year, and even that is a level very few engineers ever reach.
The $300 million pay packages Wired reported Zuckerberg dangling in front of OpenAI staff, and the reported $250 million deal for researcher Matt Deitke, are named-individual poaches for people with years of frontier research reputation already built.
They are not what opens up when you submit an application.
If you're a normal developer, the honest path is the one that's actually scalable: build real AI engineering skill, ship visible work, and go after the much larger AI engineer market first.
A seat at MSL, SSI, or Microsoft's superintelligence team is a legitimate stretch goal once you're already the kind of engineer labs go looking for, not a starting point.
The honest path into a frontier lab isn't applying harder, it's becoming the kind of developer labs go looking for first. The free 5-day Rockstar Engineer Blueprint shows you how to build the visible track record that gets you noticed, whether the title says AI or Super Intelligence.
Get the Free Course5. How to Search for These Jobs, Using Both Terms
Because the rename is a government mandate, not a private hiring-board requirement, job boards won't suddenly swap "AI" for "superintelligence" across the board just because Washington changed its paperwork.
Search both terms, every time, or you'll miss half the relevant postings.
- LinkedIn and Indeed. Save searches for "superintelligence engineer," "AI research engineer," "applied AI engineer," and "machine learning engineer," not just one phrase.
- metacareers.com. Search "Meta Superintelligence Labs" directly rather than trusting third-party aggregators, which often mirror expired listings.
- SSI's Ashby board. Check Safe Superintelligence's own Ashby job board directly.
Indeed and ZipRecruiter results for "superintelligence" frequently mix in unrelated jobs that just happen to match the keyword "safe." Set a recurring weekly check instead of relying on a single saved search to surface everything. Frontier labs post in small batches, and a listing that's live Monday can be gone by Friday.
6. How to Position Your Resume and LinkedIn for Super Intelligence Roles
Don't just swap the word
Don't swap the word "AI" for "Super Intelligence" on your resume and call it positioning. Recruiters at MSL, SSI, and Microsoft's superintelligence team know their own branding history better than a candidate who picked it up from a news cycle, and a cosmetic word swap reads as exactly that.
A seat at MSL, SSI, or Microsoft's superintelligence team is a legitimate stretch goal once you're already the kind of engineer labs go looking for, not a starting point.
What actually moves you toward these roles is the same thing that gets any strong engineer noticed: real, visible work. Public GitHub projects doing model evaluation, fine-tuning, or agent orchestration.
Writing that shows you understand how these systems actually fail and improve, not just that you can call them "super intelligence."
For the research-scientist tier, that means a publication or research record. For the applied and engineering tier, it means shipped systems a hiring manager can go look at before they ever read your resume.
What gets you noticed at SSI
SSI in particular recruits by reputation, not application volume, so the LinkedIn profile that gets you noticed there looks nothing like a keyword-stuffed resume. It looks like a track record a researcher at that company would recognize.
If you want the fuller picture on what these roles actually require and pay across levels, the super intelligence engineer guide and the super intelligence engineer salary breakdown go deeper than any single job posting will.
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