← Risk register SOC 17-3025 · reviewed 2026-08-11

Environmental Engineering Technologists and Technicians

12,190 US workers · median $59,920/yr · Engineering

EXPOSED

Roughly half this job is field work AI cannot touch — collecting soil, water, air and stack samples, installing and calibrating monitoring equipment, walking remediation sites and treatment plants, checking that installed pollution controls match the design. The other half is exactly what language models eat: drafting permit applications and compliance reports, tabulating monitoring data against regulatory limits, summarizing sampling results, maintaining records. The technician does not sign the filing — a licensed PE does — so there is no personal liability shield, which is why the desk half of the role is genuinely exposed.

10-year outlook: Headcount holds roughly flat but the mix shifts hard: report-drafting and data-compilation hours collapse into AI-assisted workflows, while sampling, instrument calibration and site oversight become the whole job.

US employment, 2019–2025-32.3%
18,01012,190 workers

Part 2020 shock, part continued decline in the years since.

Median pay $50,620 → $59,920 -5.3% in real terms (nominal +18.4%, less ~25% US inflation over the period)

The job count is not the verdict

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

+1.2% 12,900 → 13,000 on the projections basis

Exposed, but growing

AI can already do a lot of these tasks, and the BLS still expects +1.2% more of these jobs by 2034. Demand for the output is growing faster than the work is being automated away — the mechanism BLS gives for software developers, and the combination people most often misread as an error.

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.

~1,100 openings a year on average, including replacing people who leave.

One email if this score changes. Watch as many occupations as you like from the same address — no account, and nothing is sent on a schedule, only when a verdict actually moves.

Also known as — 24 job titles this covers

Titles reported by people doing this work, from the US Department of Labor's O*NET survey. If your job title is here, this page is about your work even though the name doesn't match.

Air AnalystAir TechnicianSoil TechnicianField TechnicianQuality TechnicianEngineer TechnicianPrograms TechnicianAir Moving TechnicianSoil Field TechnicianEngineering TechnicianAir Analysis TechnicianAir Pollution SpecialistEnvironmental TechnicianEnvironmental Field LaborerPollution Control TechnicianEnvironmental Engineering AideEnvironmental Field TechnicianEnvironmental Field Team MemberHaz Tech (Hazardous Technician)Intake Technician (Intake Tech)Environmental Field ProfessionalAir Quality Instrument SpecialistAquatic Technician (Aquatic Tech)Water Pollution Control Technician

Score — 41/100 resistance

Holding it up: embodiment (13/20). Weakest point: liability shield (5/20).

Five dimensions, 0–20 each, summed. Higher means more protected. The arithmetic is shown so you can check it: 9 + 13 + 5 + 6 + 8 = 41. · Scored 2026-08-11, and re-examined when evidence accumulates rather than on a schedule.

Task resistance 9/20

Mixed — a routine tier and a judgment tier At 9 the split is real: NPDES discharge monitoring reports, Title V deviation logs, and Method 25A stack test writeups are template-driven text a model drafts from the raw data file, while nobody automates lowering a bailer into a monitoring well or swapping a hi-vol filter in February — a 9 rather than 13 because even the field half is procedure-scripted (EPA SW-846, chain-of-custody forms) rather than judgment-scripted.

Embodiment 13/20

Hands-on in uncontrolled environments 13 reflects that sampling rounds happen where the contamination is — active landfills, Superfund cuts, confined-space wet wells, elevated stack platforms requiring fall protection and often 40-hour HAZWOPER — but it stops at 13 because a substantial share of days are spent in a lab or at a desk reducing the data you collected, unlike a field-only inspector.

Liability shield 5/20

Certification preferred, not legally required 5 rather than 0 because the certifications that gate parts of this work are real — HAZWOPER, state wastewater operator grades, NIOSH 582 for asbestos air sampling, DOT hazmat shipper training — but none of them is a licence that makes you personally answerable for a permit determination; the PE seal and the responsible official's signature on the Title V certification carry that.

Trust premium 6/20

Some relationship component 6 fits because you build working familiarity with the plant operators, the state DEQ inspector, and the client's EHS manager over repeat sampling visits, and being the person who knows where the sample ports are has value — but the deliverable is a defensible number in a lab-validated dataset, and the client would accept it from a different technician at the same firm next quarter.

Judgment & accountability 8/20

Meaningful discretion 8 sits above pure procedure because you decide when a sample is invalid, whether a matrix spike recovery kills the batch, when field conditions mean the run gets aborted, and when an exceedance gets escalated same-day — but the exceedance interpretation, the remedy selection, and the notification-to-agency call go up the chain to the project engineer, so you own the data quality, not the consequence.

Confidence: medium · reviewed 2026-08-11 · how scoring works

What this job involves — and which parts are yours

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.

AI already does these at usable quality

These still need a person

Active moats on the surviving side: embodiment, physical-presence

How to future-proof this job

Training paths for your skill gaps: Khan Academy — mathematics, arithmetic through calculus free · MIT OpenCourseWare — operations management free · MIT OpenCourseWare — problem-solving and analytical method courses free · CS50x, Harvard — how software is actually built free · edX — systems thinking and evaluation methods free to audit · Purdue OWL — the standard reference for professional writing free · Coursera — project coordination and cross-team delivery free to audit · Coursera — decision making under uncertainty free to audit

All 35 skills ranked by how many jobs they open →

Where this experience transfers — occupations you could move toward

Computed from U.S. Dept. of Labor O*NET skill and knowledge profiles: high overlap with what you already do, a materially higher resistance score, no large jump in required training, and no licence you would have to start a new pipeline to get. Targets that pay meaningfully less, that are themselves COOKED, or whose own headcount is falling are excluded — a move into a shrinking trade is not an escape.

Nuclear Engineers EXPOSED · 57/100 · you already have ~78% of the skill profile

Skills to close: Mathematics, Operations Analysis, Complex Problem Solving, Technology Design

Agricultural Engineers EXPOSED · 52/100 · you already have ~72% of the skill profile

Skills to close: Systems Evaluation, Writing, Complex Problem Solving, Mathematics

Architectural and Engineering Managers EXPOSED · 56/100 · you already have ~69% of the skill profile

Skills to close: Complex Problem Solving, Writing, Coordination, Judgment and Decision Making

What would move this back up — beyond any one person

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 57/100, still EXPOSED.

5 specific changes that would raise this score
  • already happening task resistance +4

    Task-mix shift: this role genuinely has two tiers. If permit drafting, limit tabulation and monitoring-report boilerplate are absorbed by AI, what remains is field sampling, equipment calibration and troubleshooting, and anomaly investigation — deciding whether an exceedance is real or an instrument drift. The measured score for the residual job rises even though total headcount may fall

  • already happening embodiment +2

    Growth in confined-space, stack, and PFAS/emerging-contaminant sampling where sub-part-per-trillion work requires meticulous manual field blank and equipment blank protocols that resist robotic handling; EPA's PFAS drinking water rule (2024) is already expanding this sampling workload

  • plausible liability shield +4

    EPA/state chain-of-custody and data-integrity rules that require a named, individually certified sampler to attest to each sample (already partial: NELAP/TNI lab accreditation, state-certified operator rules, EPA Method 25/stack-testing 'qualified individual' requirements under 40 CFR 60 Appendix A, and ASTM E1527 Phase I ESA 'environmental professional' attestation). If field sampling attestation becomes a personal certification signature — e.g. a state requiring a certified sampler's name and license number on every groundwater monitoring event for RCRA/CERCLA sites — the field half gains a shield the desk half never had

  • plausible liability shield +3

    State licensure of the sampler/technician tier itself, following the existing model for wastewater and drinking-water treatment operators (Grade I-IV state operator certification under SDWA/CWA) being extended to remediation-site and air-monitoring technicians

  • plausible judgment accountability +3

    Formal ownership of the QA/QC decision: if EPA data-quality objectives guidance or state audit practice makes a named technician responsible for accepting or rejecting a sampling event, flagging holding-time violations, and declaring data usable — the call that determines whether a site is deemed clean — the ambiguity call sits with this role rather than the PE

The limit. Trust premium has no realistic route — buyers are regulators and clients purchasing a compliant filing, and none of them pay extra for a human technician. The liability levers all attach to the field half; the desk half stays exposed regardless, so realistic ceiling is roughly the low-to-mid 50s.

These are conditions, not forecasts — what would have to happen, not what will. Specific rules, cases and bills are named so you can go and check whether they exist and where they stand; verify before relying on any of them. Nothing here is legal or financial advice.

Where this work is, and what it pays there

BLS metro figures for 61 areas. The verdict above does not change by city — the rubric judges what the work involves, not where it happens — but pay and headcount do, and the national median hides a very wide range.

Most of these jobs

Houston-Pasadena-The Woodlands, TX 670 $57,150 -5%
Atlanta-Sandy Springs-Roswell, GA 540 $60,500 +1%
New York-Newark-Jersey City, NY-NJ 500 $65,790 +10%
Los Angeles-Long Beach-Anaheim, CA 350 $58,830 -2%
San Diego-Chula Vista-Carlsbad, CA 340 $58,020 -3%
Riverside-San Bernardino-Ontario, CA 260 $59,340 -1%
San Francisco-Oakland-Fremont, CA 260 $85,780 +43%
Knoxville, TN 250 $91,440 +53%

Best paid

San Jose-Sunnyvale-Santa Clara, CA 160 $105,250 +76%
Seattle-Tacoma-Bellevue, WA 190 $105,070 +75%
Las Vegas-Henderson-North Las Vegas, NV 30 $92,230 +54%

Percentages are against this occupation's national median of $59,920. Counts are jobs in that metro, not vacancies. Metros where the BLS suppressed the cell are absent rather than shown as zero.

Who is actually doing this — nobody, on the record

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 41. 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.

Read that as a gap in the reporting we can see, not proof of absence — the dispatch runs on English-language feeds and misses plenty. If you know of a case, tell us, or add a field report from inside the job.

Quick take — do you do this job?

Has AI actually changed your work? One tap, anonymous, and the running tally is public. Nothing else is asked of you.

Self-reported and unverified — a sentiment signal, not a survey. One response per person per occupation; you can change your answer.

Field reports — what people say has changed

No field reports yet. A written account takes a paragraph rather than a tap, goes to an editor before it appears, and is the one thing on this page the rubric cannot produce on its own.

File a field report

Concrete beats general: a tool that arrived, a task that moved, a headcount decision you watched happen. Don't include anything that identifies you or your employer if that would put you at risk.

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