EXPOSED
The modal engineering manager splits time between technical review, budget and schedule tracking, staffing decisions, client and executive briefings, and walking labs, plants, or job sites. AI already drafts the status reports, cost roll-ups, spec comparisons, and first-pass design reviews that consume much of the week, but it cannot own a go/no-go call on a $40M program, absorb the consequence of a failed design, or negotiate scope with an owner. A meaningful minority hold PE or architect licensure and personally stamp work, which hardens their position; those managing purely as administrators are the exposed tier.
Dipped in 2020, then grew past where it started.
Median pay $144,830 → $171,270 -5.4% in real terms
This line is counted by the Bureau of Labor Statistics — the one figure on this page that isn't a judgement of ours. Headcount moves on demand, offshoring, demographics and the business cycle, and automation is one term among several, often not the loudest.
So a falling line is not evidence that AI did it, and a rising one is not evidence that it won't. Both happen in this register: some occupations resist automation and shrink anyway, others are highly automatable and keep growing. The marked year is 2020.
BLS projection, 2024–2034
+3.8% 212,500 → 220,500 on the projections basis
Growing, and only partly exposed
The BLS expects +3.8% more of these jobs by 2034, and at 56/100 the work is only partly exposed — some tasks are automatable, the core of the job is not. Nothing here is in tension.
Different clocks. The score is what current AI could do to this work today. The projection is how many of these jobs will exist in 2034. Everything between the two — how fast employers actually adopt, whether demand grows in the meantime — is why they can point opposite ways without either being wrong.
~14,500 openings a year on average, including replacing people who leave.
Project ManagerBiofuels ManagerResearch ManagerArchitect ManagerProject CoordinatorEngineering DirectorFermentation ManagerEngineering SupervisorBiofuels Product ManagerData Engineering ManagerBiodiesel Product ManagerCivil Engineering ManagerData Engineering DirectorEngineering Group ManagerBiodiesel Division ManagerEngineering Design ManagerGlobal Engineering ManagerPrototype Engineer ManagerBiofuels Technology ManagerEngineering Program ManagerEngineering Project ManagerProcess Engineering ManagerProject Engineering ManagerBiodiesel Technology Manager
Holding it up: judgment & accountability . Weakest point: embodiment .
Mixed — a routine tier and a judgment tier Earned-value roll-ups, spec comparison matrices, drawing-set completeness checks, and weekly status decks are already machine-drafted, but the same week includes design-basis arguments with a lead engineer, resource reallocation when a discipline slips, and standing in front of an owner explaining a change order — leaving it mixed rather than clearly resistant.
Some physical or field component Site walks, factory acceptance tests, punch-list reviews, and lab or plant floor visits are recurring but usually weekly-to-monthly obligations sandwiched between office days, and the manager observes rather than installs, torques, or commissions — so a physical component exists without the job living in the field.
Certification preferred, not legally required A PE stamp or registered architect seal makes the individual personally answerable under state engineering practice acts, but a substantial share of these managers direct staff without holding or exercising licensure themselves, pushing the seal onto a subordinate engineer of record — the 9 reflects that split, not a uniform licensed duty.
Exists to be accountable for ambiguous calls Go/no-go on a design release, accepting residual risk on a life-safety system, deciding whether a failed test warrants requalification or a waiver, and choosing whom to lay off during a program cut are calls made with incomplete data where the manager's name is on the record afterward.
The verdict above describes this occupation as a whole. Almost nobody does the typical version of a job — tick what's actually in your week and see how your own mix sits.
Your task mix speaks to task resistance (12/20 here) — how much of the day's work current AI already does. That is the dimension the boxes above are about.
It cannot move the other three. Liability shield (9/20) is whether the law requires a licensed human to sign. Trust premium (12/20) is whether buyers specifically pay for a person. Judgment and accountability (16/20) is whether the role exists to own consequential calls. Those are facts about the occupation's standing, not about which tasks are in your week — a paralegal who does only trial exhibits still holds no licence. Together they are 37 of this occupation's 56 points (66%).
Embodiment (7/20) is also a property of the work rather than the worker, but we don't tag individual tasks as physical or not, so the picker can't tell you anything about it. That's a limit of this tool, not a claim.
Did we get the list right? Tell us what's missing — the tasks are written from the outside, and you're reading this from the inside.
No occupation passed every test: close enough to architectural and engineering managers on skills and subject matter, at least 10 points more resistant, no big jump in training, no new licence, no pay cut, and not shrinking on its own. That happens for 223 of the 654 occupations here that aren't SAFE, and it is worth stating plainly rather than leaving the section off.
The usual reason is that exposure travels with the skill profile. The jobs most similar to yours tend to be exposed for the same reasons yours is, so the near neighbours don't clear the gap — and the ones that do are a different kind of work, not a transfer of what you already know. Read that as a limit of this method, not a verdict that you're stuck: it only compares whole occupations, and it cannot see specialisation, industry, or anything you'd bring that isn't in a federal skill survey.
Here is that claim on your own job rather than in the abstract. These are the three occupations closest to this one by skill and subject matter — the places the work would most naturally transfer — with what the register scores them:
That is the whole problem in three lines. The nearest work is not meaningfully safer, so there is no move here that trades a similar skill set for a better verdict. This is not us running out of ideas — it is what the neighbourhood looks like.
The moves above are yours to make. This is the other half: what would have to change in the world for the occupation itself to score higher. None of it is in any one person's gift, but it is where the floor actually comes from. Scores here are not a one-way ratchet. Only two of the five dimensions — task resistance and embodiment — track what machines can do. The other three track law, what buyers will pay for, and who is answerable, and those move in both directions, often in response to the same pressure AI creates. If every lever below landed, this occupation would score around 77/100 — SAFE.
A board or insurer rule that AI-generated calculations, drawings, or spec packages cannot be issued without an identified licensed human of record who attests to independent verification — analogous to professional liability carriers (e.g. Victor/AIA-endorsed policies) adding AI-use exclusions unless a named licensee reviewed the output. Turns review-and-sign into a non-delegable step.
Task-mix shift: the occupation genuinely has two tiers. If status reporting, cost roll-ups, spec comparison, and first-pass design review are fully absorbed by tooling, what remains is go/no-go on capital programs, scope renegotiation with owners, failure investigation, and staffing calls — the residual job is denser in exactly what models cannot own. The administrative-only tier shrinks rather than rising.
State board enforcement or tightening of 'responsible charge' / direct supervisory control rules so that the manager who approves AI-assisted design output must personally hold the PE or RA seal — NCEES Model Law already defines responsible charge, and several boards (TX, FL) have opened rulemaking on AI-generated engineering documents. Repeal or narrowing of the industrial exemption (live in TX and OH debates) would pull in-house plant and manufacturing engineering managers into the sealed tier.
Owner-side procurement language (state DOTs, DOE/NNSA, utility capital programs) naming a specific engineer-of-record and program manager as key personnel who cannot be substituted, with resumes scored — plus FAR/agency clauses requiring disclosure of AI use in deliverables. Buyers then pay explicitly for the named human's judgment, not the firm's tooling.
Site-presence requirements written into permits and safety regimes — e.g. OSHA or state requirements for a qualified/competent person physically on site for commissioning, confined-space, or energized work, and utility/nuclear regimes requiring a named responsible engineer walkdown before startup. Raises the floor only for the subset managing plants, construction, and labs.
The limit. judgment_accountability at 16 is already near its practical ceiling; owning consequential calls is the core of the role and there is no institutional change that meaningfully adds to it. Note also that most of the liability_shield upside accrues only to the licensed minority — for administrator-track managers with no PE or RA, none of the shield levers apply and there is no visible route to one without licensure itself.
| Los Angeles-Long Beach-Anaheim, CA | 9,570 | $190,900 +11% |
| Detroit-Warren-Dearborn, MI | 9,260 | $168,550 -2% |
| New York-Newark-Jersey City, NY-NJ | 7,580 | $183,890 +7% |
| Boston-Cambridge-Newton, MA-NH | 6,690 | $205,130 +20% |
| Chicago-Naperville-Elgin, IL-IN | 6,670 | $163,430 -5% |
| Dallas-Fort Worth-Arlington, TX | 5,970 | $172,160 +1% |
| Washington-Arlington-Alexandria, DC-VA-MD-WV | 5,500 | $185,220 +8% |
| Houston-Pasadena-The Woodlands, TX | 5,330 | $172,020 +0% |
| San Jose-Sunnyvale-Santa Clara, CA | 5,130 | $234,590 +37% |
| San Francisco-Oakland-Fremont, CA | 5,000 | $221,580 +29% |
| Albuquerque, NM | 1,160 | $215,120 +26% |
We have no reported case of a named organisation automating this occupation. Not one deployment, not one announcement.
That is worth saying out loud next to a score of 56. The verdict above is about what the work exposes — what current AI could do to these tasks. It is not a claim that anyone has done it. For this occupation those two things have come apart completely: the capability argument is on this page, and the evidence column is empty.
Has AI actually changed your work? One tap, anonymous, and the running tally is public. Nothing else is asked of you.
Rather than check back: get the digest and we'll tell you what changed — or watch a single occupation from its own page.