EXPOSED
A large share of the day is document and screen work — permit applications, NEPA and EIS narrative sections, Phase I ESA desk reviews, regulatory citation lookups, air/water dispersion model runs, and monitoring-data QA — and language models plus modeling automation already handle much of the drafting and summarizing at usable quality. What persists is the stamped remediation design, the site walk where the actual soil, tank, or outfall doesn't match the drawings, and the negotiation with EPA or a state agency over what a compliance path will be. The PE license and personal liability for signed designs are the strongest moat, and they are regulatory rather than technical.
This fall is concentrated in 2020 and has not recovered since.
Median pay $88,860 → $107,110 -3.6% 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
+3.9% 39,400 → 41,000 on the projections basis
Growing, and only partly exposed
The BLS expects +3.9% more of these jobs by 2034, and at 54/100 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.
~3,000 openings a year on average, including replacing people who leave.
EngineerSoil EngineerCivil EngineerCoastal EngineerEnvironmentalistProject EngineerSanitary EngineerReservoir EngineerIrrigation EngineerSanitation EngineerAir Quality EngineerSolid Waste EngineerEnvironmental AnalystEnvironmental PlannerEngineering ConsultantEnvironmental DesignerEnvironmental EngineerFlood Control EngineerPublic Health EngineerEnvironmental ScientistEnvironmental ConsultantSewage Disposal EngineerEnvironmental CoordinatorWaste Management Engineer
Holding it up: liability shield . Weakest point: trust premium .
Mixed — a routine tier and a judgment tier AERMOD and MODFLOW runs, Title V permit renewals, Phase I ESA records reviews, and DMR/quarterly monitoring reports are templated enough that a model plus a script covers the first draft, which is why this sits at 10 rather than 15 — the remaining half is sizing a pump-and-treat system or an SVE array against site conditions no dataset describes.
Some physical or field component You are on site for tank pulls, soil boring oversight, outfall and stack-test observation, and post-remediation confirmation sampling, but that is weeks a year in steel toes and a hard hat rather than daily — the bulk of the work happens back at a desk, which puts it at 9 instead of the 14+ a field geologist or industrial hygienist would earn.
Licensed human required and personally liable The PE stamp on a remediation design, a stormwater or landfill closure plan, or a treatment-system spec is a personal legal exposure under state engineering practice acts, and NPDES and RCRA filings name a responsible engineer — 13 not higher because plenty of environmental engineering work (ESAs, permit support, compliance auditing) is legally performed unstamped by staff who never sit for the PE.
Meaningful discretion Calling a site closed under a risk-based cleanup standard, choosing MNA over active remediation, or deciding a release is reportable under CERCLA 103 are consequential judgments with imperfect data and real downside — 13 rather than 17 because most of these choices are bounded by promulgated cleanup levels, state guidance documents, and a client and agency who both sign off before anything moves.
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 (10/20 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 (13/20) is whether the law requires a licensed human to sign. Trust premium (9/20) is whether buyers specifically pay for a person. Judgment and accountability (13/20) 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 35 of this occupation's 54 points (65%).
Embodiment (9/20) 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.
Construction Managers EXPOSED
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 68/100 — SAFE.
Task-mix shift is genuine here: if the permit-narrative, citation-lookup, and monitoring-data QA tier is automated, the residual job is stamped remediation design, agency negotiation over compliance paths, and site-walk reconciliation where as-builts are wrong. That raises measured resistance while shrinking headcount
Professional liability insurers (Victor/AXA XL, Beazley E&O for A/E firms) adding endorsements that exclude coverage for deliverables where AI tools were used without documented engineer verification, making a signing human contractually mandatory on every remediation design and Phase I ESA — AI exclusions are already appearing in 2024-25 E&O renewals
State engineering boards adopting explicit rules that AI-generated design or model output must be reviewed and sealed by a PE who performs independent verification — NCEES and several state boards (e.g., Texas, North Carolina) have opened rulemaking on 'responsible charge' and AI tools; a rule barring AI output from counting as the engineer's own work product, plus EPA/state DEQ permit forms requiring a named PE-of-record for dispersion modeling and remedial design submittals, would tighten the seal requirement
CERCLA/RCRA and state voluntary cleanup programs increasingly requiring a Licensed Site Professional-style role that personally certifies closure — the Massachusetts LSP and Connecticut LEP models — expanded to more states, placing the no-further-action call and its reopener risk on a named individual
ASTM E1527 Phase I revisions or state cleanup programs requiring documented in-person site reconnaissance by the environmental professional (not a subcontracted technician or drone/imagery substitute), plus PFAS and vapor-intrusion sampling protocols that require judgment-driven on-site sampling point selection
The limit. Trust premium has no plausible route: clients are corporate real-estate and industrial buyers who purchase a stamp and a defensible file, not a human relationship, and they price-shop consultants. Practical ceiling is roughly high-60s, driven almost entirely by license and personal-certification rules, not by anything AI cannot do.
| New York-Newark-Jersey City, NY-NJ | 1,810 | $107,910 +1% |
| Boston-Cambridge-Newton, MA-NH | 1,460 | $109,620 +2% |
| Sacramento-Roseville-Folsom, CA | 1,200 | $133,240 +24% |
| Seattle-Tacoma-Bellevue, WA | 1,050 | $128,410 +20% |
| Philadelphia-Camden-Wilmington, PA-NJ-DE-MD | 1,040 | $129,390 +21% |
| Denver-Aurora-Centennial, CO | 910 | $107,880 +1% |
| Los Angeles-Long Beach-Anaheim, CA | 890 | $127,900 +19% |
| Washington-Arlington-Alexandria, DC-VA-MD-WV | 810 | $120,580 +13% |
| Cape Coral-Fort Myers, FL | 50 | $142,700 +33% |
| Santa Rosa-Petaluma, CA | 100 | $141,560 +32% |
| Redding, CA | 40 | $140,570 +31% |
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 54. 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.