red-teaming jobs in 2026 — demand, top roles hiring, and related skills
As of 2026-10-14, red-teaming appears in 242 job postings indexed by Skillenai over the past 90 days — AI Safety Evaluator has the most postings mentioning red-teaming, with demand share up 8.4% vs the prior 4 weeks.
Last updated · 90d ending 2026-10-14
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Frequently asked questions about red-teaming
+Is red-teaming in demand in 2026?
Yes. red-teaming appears in 242 job postings indexed by Skillenai over the 90 days ending 2026-10-14. AI Safety Evaluator accounts for the most postings mentioning red-teaming (6.6% of all postings mentioning red-teaming).
+What jobs require red-teaming?
According to the Skillenai jobs index over the 90 days ending 2026-10-14, among roles with at least 20 postings, the highest shares mentioning red-teaming are AI Safety Evaluator (57.1% of that role’s postings mention red-teaming), Application Software Engineer (16.0% of that role’s postings mention red-teaming), GRC Engineer (9.5% of that role’s postings mention red-teaming).
+What skills are commonly paired with red-teaming?
Across job postings indexed by Skillenai (90 days ending 2026-10-14), red-teaming most often appears alongside Python, adversarial testing, prompt injection, threat modeling, Content moderation.
+Where is red-teaming most in demand?
As of 2026-10-14, the metro areas posting the most jobs requiring red-teaming are San Francisco, New York City, London, Ho Chi Minh City, Washington, according to the Skillenai jobs index.
+How can I keep up with new red-teaming content and jobs?
Skillenai indexes news, blog posts, and research papers mentioning red-teaming alongside the jobs index. You can subscribe to a daily email digest of new red-teaming content from your Skillenai account.
+Which skills come before and after red-teaming?
The skill-flow chart shows skills documented in adjacent positions across observed employer changes. An outgoing skill is documented in the following position but not the preceding one. These are ideas to explore, not proven prerequisites, acquisition dates, or levels of mastery. Each ribbon counts employer moves with that skill pair; one move can contribute several pairs.
Weekly indexed postings requiring red-teaming — last 90 days
Salary distribution
Box = 25th–75th percentile · tick = median · whisker = 10th–90th · USD, annualized
Career paths around red-teaming
Skills documented before and after this skill across employer changes.
Not enough linked career history to draw this chart yet.
Roles most likely to require red-teaming
Among roles with at least 20 postings in the same period.
| Role | Postings mentioning skill | % of role postings mentioning skill |
|---|---|---|
| AI Safety Evaluator | 16 | 57.1% |
| Application Software Engineer | 8 | 16.0% |
| GRC Engineer | 2 | 9.5% |
| AI Security Researcher | 2 | 8.3% |
| AI Security Engineer | 12 | 7.7% |
| Postdoctoral Researcher | 1 | 4.5% |
| AI Security Specialist | 1 | 4.0% |
| Applied Research Scientist | 1 | 3.7% |
| Chief Information Security Officer (CISO) | 1 | 3.7% |
| AI Tech Architect | 1 | 3.4% |
Roles with the most red-teaming postings
| Role | Postings mentioning skill | Share of skill postings |
|---|---|---|
| AI Safety Evaluator | 16 | 6.6% |
| AI Security Engineer | 12 | 5.0% |
| Research Scientist | 11 | 4.5% |
| Security Engineer | 11 | 4.5% |
| AI Safety Evaluation Expert | 9 | 3.7% |
| Software Engineer | 9 | 3.7% |
| AI Engineer | 8 | 3.3% |
| Application Software Engineer | 8 | 3.3% |
| Product Manager | 8 | 3.3% |
| AI Security Software Engineer | 6 | 2.5% |
Top companies posting jobs requiring red-teaming
Employers ranked by indexed job postings in the last 90 days.
| Company | Postings · 90 days |
|---|---|
| OpenBrain | 33 |
| SpaceX | 18 |
| Bosch | 9 |
| Samsara | 9 |
| Anthropic | 8 |
| Scale AI | 8 |
| Mercor | 6 |
| OpenAI | 5 |
| BCG | 5 |
| Apollo Research | 5 |
Job postings indexed over the past 90 days, grouped by resolved employer. Counts are postings, not hires. Companies without a published page appear without a link.
Top metros hiring for red-teaming
| Name | Postings | Share |
|---|---|---|
| San Francisco | 25 | 10.3% |
| New York City | 13 | 5.4% |
| London | 11 | 4.5% |
| Ho Chi Minh City | 9 | 3.7% |
| Washington | 7 | 2.9% |
| Palo Alto | 6 | 2.5% |
| Hawthorne | 4 | 1.7% |
| Boston | 2 | 0.8% |
| Cape Canaveral | 2 | 0.8% |
Skills commonly paired with red-teaming
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How this was computed
Counts derive from the Skillenai jobs index over the 90 days ending 2026-10-14. Skills are resolved against the Skillenai canonical taxonomy, so the same entity is counted whether a posting writes 'Python', 'Python 3', or 'python'. Role prevalence divides postings mentioning red-teaming by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s red-teaming postings by all red-teaming postings, including postings without a role. Shares need not sum to 100% for the displayed roles. Pages refresh weekly (or daily for the top-50 most-requested skills). Adjusted posting share: 0.1% to 0.1%. Demand share change is the relative percentage change between these adjusted shares. Each employer-and-ATS group has at least 10 postings in each 90-day window; its earlier posting count supplies the same weight in both windows. The panel includes 2,614 identified employers and covers 71% of earlier and 72% of latest indexed postings. Windows: 2026-06-16 to 2026-09-14 and 2026-07-14 to 2026-10-12 (UTC; end dates excluded). The windows overlap by 62 days. Dates reflect indexing, not the employer’s posting date. This measures posting mix, not total hiring or market-wide demand. Matching excludes entrants and exits; changes in crawl completeness within an employer or ATS can still affect the result.
- source
- Skillenai jobs index, deduplicated daily
- entity_id
- 34457a4331267878
- data_as_of
- 2026-10-14
- window_days
- 90
The demand, skills, and geo numbers on this page come from the same Skillenai labor market index that powers our API. Use it for compensation benchmarking, hiring-competition analysis, and skill-adoption tracking.
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