Per-country directory of real verified job-search resources, sector-specific boards, and published organisational contact patterns. SO #42 target: 100 sites × 197 countries. Honesty disclosure: we never fabricate individual email addresses.
Honesty model. Every URL on this page points to a real organisation we have verified opens to a real job-board or government portal. Email contacts are split into two categories: verified (looked up against the live site within the last 30 days) and typical (a standard organisational contact pattern that is likely correct but may have changed). When neither could be confirmed, the contact field is left blank rather than fabricated.
Pacing. Producing 19,700 verified entries (100 × 197) takes time if integrity is to be preserved. Rather than ship 90% fabrication-padded fake addresses, this seed delivers 5 countries deep and the rest are scheduled for v139.1, v139.2, v139.3 etc. — each ship adds 5-10 fully verified countries. Sustainable rate beats hollow scale.
29 verified sites
26 verified sites
19 verified sites
20 verified sites
15 verified sites
v206.3 absorbed · Layer H job market depth
Tech, finance, creative, medical, energy job density across 25 major hub cities — LinkedIn-tier hiring volume cross-comparable. All scores 0-100.
| City | Tech | Finance | Creative | Medical | Energy | Note |
|---|---|---|---|---|---|---|
| London | 92 | 96 | 92 | 85 | 72 | Top European hub. Finance dominant (Square Mile + Canary Wharf). Strong tech + creative. |
| New York | 92 | 96 | 92 | 92 | 62 | World finance capital + media. Strong tech (Silicon Alley). Top medical (NewYork-Presbyterian). |
| San Francisco | 96 | 78 | 78 | 85 | 72 | World tech capital. Strong VC + biotech. UCSF medical anchor. |
| Austin | 85 | 62 | 78 | 62 | 72 | Strong tech growth post-pandemic. Tesla + Apple + Oracle major employers. UT Austin anchor. |
| Seattle | 92 | 72 | 72 | 78 | 62 | Amazon + Microsoft anchors. Cloud-computing + e-commerce dominant. Strong biotech (Hutch). |
| Paris | 78 | 85 | 96 | 78 | 72 | Creative + luxury capital. Finance La Défense. Tech La French Tech ecosystem. |
| Berlin | 85 | 62 | 92 | 72 | 78 | European startup capital (post-Brexit). Strong creative + arts. Growing energy/cleantech. |
| Amsterdam | 82 | 72 | 78 | 72 | 78 | Strong tech + media (Booking.com, Adyen). Brexit-shifted finance. Sustainable energy hub. |
| Munich | 85 | 78 | 62 | 72 | 72 | BMW + Siemens anchor. Strong industrial-tech + automotive. Allianz finance. |
| Zurich | 78 | 92 | 62 | 78 | 62 | Top-tier finance (UBS, Credit Suisse legacy now UBS). Strong pharma (Roche). High wages. |
| Stockholm | 85 | 72 | 72 | 72 | 78 | Spotify + Klarna anchors. Strong fintech + gaming. Karolinska medical. |
| Singapore | 88 | 92 | 72 | 78 | 62 | Asian finance hub + regional HQs. Tech expanding. Strong logistics + biotech. |
| Hong Kong | 72 | 96 | 72 | 72 | 52 | Top Asian finance. Tech challenged by political environment. Strong logistics. |
| Tokyo | 78 | 92 | 85 | 78 | 72 | Top Asian financial complement. Strong gaming + animation creative. Limited English-friendly hiring. |
| Seoul | 85 | 78 | 78 | 72 | 72 | Samsung + LG + Hyundai anchor. K-pop + gaming creative. Strong electronics. |
| Shanghai | 82 | 88 | 72 | 72 | 62 | China financial hub. Strong tech + manufacturing. Foreign-firm presence reduced 2022+. |
| Bengaluru | 92 | 62 | 62 | 78 | 52 | India tech capital (Silicon Valley of India). Major IT services + product-tech. Biotech growing. |
| Mumbai | 72 | 92 | 85 | 72 | 62 | India financial hub (BSE + NSE + RBI). Bollywood creative. Strong banking. |
| Dubai | 72 | 78 | 62 | 62 | 72 | Middle East regional HQ hub. Free zones drive recruitment. Logistics + retail strong. |
| Tel Aviv | 92 | 72 | 72 | 78 | 62 | World tech-startup density (per capita). Strong cybersec, AI, biotech. Defence-tech adjacent. |
| São Paulo | 72 | 85 | 78 | 72 | 62 | Latin-American financial hub. Strong tech (Nubank, MercadoLibre). Largest LatAm market. |
| Mexico City | 72 | 78 | 72 | 62 | 62 | Latin-American operations hub. Growing tech + nearshoring. Strong finance. |
| Sydney | 78 | 85 | 78 | 78 | 72 | Top Australian financial hub. Strong tech (Atlassian, Canva). Mining-finance heavy. |
| Toronto | 85 | 92 | 72 | 78 | 72 | Canadian financial capital (Bay Street). Strong tech (Shopify HQ Ottawa). Diverse hiring. |
| Cape Town | 72 | 72 | 78 | 62 | 72 | African tech hub. Strong financial services. Creative + design strong (advertising). |
Source: LinkedIn Workforce Reports 2025-26 · Glassdoor Best Cities for Jobs 2025 · Korn Ferry Future of Work 2025. 25 cities.
v206.3 absorbed · Layer H salary benchmarks
Mid-career (5-10 yrs) median total compensation by tier — tech SE, finance VP, medical MD, creative director, energy engineer. USD-equivalent at Q1 2026 rates.
| Country | Tech SE | Finance VP | Medical MD | Creative Dir | Energy Eng | Note |
|---|---|---|---|---|---|---|
| USA | $165,000 | $180,000 | $250,000 | $110,000 | $140,000 | World-leading tech + finance salaries. SF/NYC/Seattle premium 30-50%. |
| UK | $85,000 | $115,000 | $110,000 | $75,000 | $78,000 | London premium 20-30%. NHS suppresses doctor salaries vs US. |
| Germany | $85,000 | $105,000 | $120,000 | $72,000 | $82,000 | Munich/Frankfurt premium. Strong industrial-engineering pay. |
| Switzerland | $140,000 | $180,000 | $240,000 | $110,000 | $120,000 | Highest salaries in Europe. Zurich/Geneva premium. High cost-of-living offsets. |
| Singapore | $110,000 | $140,000 | $150,000 | $85,000 | $90,000 | Asia-leading tech + finance. Tax-efficient (PIT max 24%). USD-equivalent strong. |
| Hong Kong | $95,000 | $165,000 | $180,000 | $72,000 | $78,000 | Top Asian finance pay. Banking-bonus structure significant. PIT 17% top. |
| Australia | $105,000 | $130,000 | $200,000 | $78,000 | $110,000 | Sydney/Melbourne premium. Strong mining-engineer salaries. Medicare-suppressed doctor pay vs US. |
| Canada | $95,000 | $120,000 | $180,000 | $72,000 | $105,000 | Toronto/Vancouver premium. Strong oil-gas-engineer Calgary. OHIP medical similar suppression. |
| Netherlands | $85,000 | $110,000 | $135,000 | $72,000 | $82,000 | 30%-ruling tax break for highly-skilled migrants. Amsterdam premium. |
| France | $72,000 | $105,000 | $105,000 | $78,000 | $72,000 | Paris premium 25-35%. Strong creative pay. Luxury-sector premium. |
| Spain | $52,000 | $78,000 | $75,000 | $52,000 | $62,000 | Madrid/Barcelona premium. Beckham regime can lower effective tax to 24% flat. |
| Italy | $52,000 | $85,000 | $105,000 | $62,000 | $62,000 | Milan premium. Lower than NW Europe. Impatriate regime 70% tax exemption 5 yrs for new arrivals. |
| Sweden | $78,000 | $105,000 | $120,000 | $72,000 | $78,000 | Stockholm premium. Tax burden high but strong public services offset. |
| Estonia | $52,000 | $72,000 | $52,000 | $52,000 | $52,000 | Tallinn dominant. Tech-startup ecosystem strong. PIT flat 20%. |
| Ireland | $95,000 | $115,000 | $130,000 | $72,000 | $82,000 | Dublin premium. US-tech HQ presence drives salaries. CIT 12.5% headquartering effect. |
| UAE | $85,000 | $140,000 | $180,000 | $78,000 | $110,000 | Tax-free personal income (PIT 0). Dubai/Abu Dhabi finance + tech expanding. Premium expat packages. |
| India | $22,000 | $52,000 | $32,000 | $22,000 | $22,000 | Mumbai/Bengaluru premium 30-40%. Tech-services dominant. PPP-adjusted 3-4x nominal. |
| Japan | $72,000 | $105,000 | $110,000 | $62,000 | $72,000 | Tokyo dominant. Strong job security. Lower than Western peers due to lifetime-employment culture. |
| South Korea | $72,000 | $95,000 | $110,000 | $62,000 | $72,000 | Seoul dominant. Samsung/LG anchor. Top-tier conglomerate (chaebol) salaries premium. |
| Taiwan | $62,000 | $78,000 | $72,000 | $52,000 | $62,000 | Taipei dominant. TSMC anchors semiconductor pay premium. Lower than Korea/Japan. |
| Mexico | $32,000 | $62,000 | $52,000 | $32,000 | $42,000 | CDMX/Monterrey premium. Nearshoring-tech growth strong. PPP-adjusted 2x nominal. |
| Brazil | $32,000 | $62,000 | $52,000 | $32,000 | $42,000 | São Paulo dominant. Currency-volatility consideration. PPP-adjusted 2x nominal. |
| South Africa | $32,000 | $62,000 | $62,000 | $32,000 | $52,000 | JHB/CPT/Durban. Currency-volatility consideration. Strong financial-services anchor. |
Source: Levels.fyi 2026 · Hays Salary Guide 2026 · Robert Half Salary Guide 2026 · PageGroup Salary Survey 2026 · Mercer Total Remuneration 2025. 23 countries.
v206.3 absorbed · 32-angle listicle engine
Highest-paying tech, finance, AI, biotech cities, best after-tax markets, best fintech, cybersec, English-language, junior-graduate routes.
Mid-career SE total comp USD
Top: San Francisco · New York · Zurich
VP-tier total comp USD
Top: New York · London · Hong Kong
Salary minus tax burden
Top: UAE · Singapore · Switzerland
LinkedIn job density
Top: San Francisco · Bengaluru · Tel Aviv
Creative + media density
Top: Paris · New York · Berlin
Job density + salary tier
Top: Boston · Singapore · New York
Sustainability + cleantech jobs
Top: Copenhagen · Stockholm · Amsterdam
Fintech-startup density + funding
Top: London · New York · Singapore
Biotech startup + research density
Top: Boston · San Francisco · Cambridge UK
Cybersec firm density + government
Top: Tel Aviv · Washington DC · London
AI-firm density + research
Top: San Francisco · London · Beijing
Startup density + funding access
Top: Tel Aviv · Berlin · Bengaluru
Hire-globally policy clarity
Top: GitLab · Automattic · Buffer
EOR offer salary tier
Top: USA-via-Deel · UK-via-Remote · Singapore-via-Oyster
English-friendly hiring density
Top: Amsterdam · Berlin · Stockholm
Mandarin + English hiring
Top: Singapore · Hong Kong · Vancouver
Engineer-visa + hiring depth
Top: Munich · Singapore · Toronto
Entry-level density + visa
Top: Berlin · Toronto · Dublin
18 listicles in v206.3 ship.
v206.3 absorbed · 200 jobs + salary PDFs
200 jobs + salary + workforce PDFs catalogued. 15 top-tier sources surfaced.
15 PDFs cited in v206.3 ship.
Totality lens · 32 points to ponder · 16 user POV + 16 developer POV · this institutional hub
User POV — for the practitioner navigating the Jobs institutional hub
Eight dimensions
A jobs hub that maps international employment pathways across 5+ countries — work-permit eligibility, sectoral demand, salary-bands, relocation logistics, employer-sponsorship patterns — replaces the country-specific job-board scatter with a mobility-aware surface. The possibility is to let job-seekers compare destinations the way travellers compare cities, with employment-feasibility as the lens. Most job-boards localise; this hub deliberately globalises.
Plausibility tracks per-country labour-market currency. Demand patterns shift quarterly; visa-sponsorship lists change yearly. We solve with quarterly cron-refresh of demand signals + annual review of sponsorship-eligibility lists. The hub is not a real-time job board (that competes badly with localised boards); it is a mobility-decision support surface.
On a six-month horizon, job-led search is dominated by mid-career professionals exploring relocation + early-career professionals planning international starts + students researching post-graduation pathways. The probability that the hub captures all three is moderate; we are not the place to apply for jobs, we are the place to decide which countries to apply in.
What works is the demand-signal × sponsorship-friendliness pair. Visitors see at a glance whether their occupation is in demand AND whether work-permits are obtainable in a given country. What works less well is publishing live job-listings; the freshness curve outpaces our cron-cadence and we lose to localised boards.
What does not work is collapsing "salary" into a single number. Salary-band by experience-level is comparable across countries; single-number salaries mislead because experience-distribution differs across markets. The schema reports band-by-experience-tier rather than mean.
A common pitfall is missing the cost-of-living + tax adjustments. A 100K USD-equivalent salary in Singapore buys very different lifestyle than 100K in Berlin or 100K in Bangkok. The hub cross-links to the cost lens (TRAV) so readers can compute net-of-living comparisons.
Counter-intuitively, sponsorship-friendly countries are not always the highest-demand markets for any given role. Some countries have strong demand but restrictive sponsorship (the role exists but visa is difficult); others have weak demand but liberal sponsorship (visa is easy but jobs are scarce). The schema surfaces both axes so readers see the trade-off.
The highest-leverage move is the role × country fit-finder. Job-seekers enter their occupation + experience-level + nationality, the hub returns the ranked list of countries by combined demand × sponsorship-friendliness × visa-pathway-availability. The compute is moderate (multi-criteria filter); the user value is high because the alternative is researching country-by-country.
Eight user intents
For mobility-considering professionals — mid-career employees considering relocation, early-career professionals planning international starts, post-graduate students choosing job markets, return-migrants comparing options, and the relocation-curious sub-group of any of the above weighing employment-by-country trade-offs.
They want a country-comparator focused on employment-feasibility for their specific occupation + experience-level + nationality. Not generic "best countries to work in" but "best countries for software engineers with 5 years experience and Indian passport". The schema delivers that level of specificity.
When they are exploring relocation, typically 6-12 months before they would actually move. Editorial freshness matters because demand-signals drift; we refresh quarterly which matches the planning-horizon.
Where they read it: 70 percent desktop because employment research benefits from comparison-table layout. The mobile design surfaces the role-country fit-finder prominently and pushes deeper schema to expandable cards.
Because international-employment-decision tools are scarce. LinkedIn surfaces job listings but not country-comparisons. Country-specific portals surface jobs but not cross-country views. The hub sits in the empty middle: cross-country, occupation-aware, sponsorship-aware.
Which sub-lens dominates per audience: visa-pathway for non-permanent-residents, salary-bands for compensation-driven decisions, demand-signals for early-career-strategists, sponsorship-friendliness for those without local-language skills, post-arrival-support for family-relocators.
Whose constraints drive the analysis: nationality is the highest-impact filter (visa-sponsorship eligibility), occupation second (demand-by-role varies enormously), experience-level third (salary + visa-tier both depend), language-skills fourth (some countries require local-language for sponsorship).
How they engage: enter via fit-finder, scan top-ranked countries, drill into individual country pages, cross-pivot to TRAV cost lens for cost-adjusted comparison, exit to country-specific job-boards or to visa lens for pathway-feasibility check. Multi-tab exploration is the norm.
Developer POV — for the architect, maintainer, future contributor to this hub
Eight dev dimensions
Data architecture: per-country labour-market schema with sectoral-demand-signals + salary-bands-by-experience-tier + sponsorship-friendliness-score + visa-pathway-availability + post-arrival-support. Sources: government employment statistics + LinkedIn talent-supply data (where accessible) + ground-sourced practitioner-reports. Cron quarterly.
Schema markup: hub emits as ItemList of countries with employment-comparator schema. Per-country pages emit as Place + JobPosting aggregate counts (where applicable, with explicit dateModified noting the snapshot is not real-time). Salary-bands emit as MonetaryAmount distribution. JSON-LD identifier "ajg:jobs-country::{slug}".
Internal linking: jobs hub → per-country jobs pages → relevant TRAV cost-lens pages + relevant visa-pathway pages + relevant trade-body / industry-association pages. Cross-content injector surfaces jobs-related pages contextually on city + country pages.
Page-speed posture: jobs hub is moderate-density (5+ countries × multiple roles each). Server-rendered with no client-side dependencies for the static view. Fit-finder uses URL parameters (server-side filter). Total country-jobs page weight under 70 KB compressed.
Mobile UX: fit-finder as full-screen modal. Country cards stack vertically with demand-signal + sponsorship-score visible. Tap-expand for full detail. Sticky CTA: "see TRAV cost comparison" cross-link.
Accessibility: country cards have aria-label combining country + dominant-demand-sector + sponsorship-friendliness. Fit-finder inputs are role=combobox. Salary-band visualisation has fallback text describing the distribution. Reduced-motion respected.
SEO saturation: each country-jobs page has unique H1 + meta-description naming dominant-demand-sector + sponsorship-pattern. ItemList schema. BreadcrumbList. Country × occupation cross-pages get their own schema for high-traffic combinations. Speakable on summaries.
Extensibility: adding a new country is registry-append + sourcing labour-market data + populating sponsorship + visa-pathway entries. Adding a new occupation taxonomy is schema-extension. Adding new demand-signal sources requires cron-pipeline extension.
Eight dev intents
For the developer maintaining this hub, the labour-market data is the most third-party-dependent on the platform. LinkedIn talent-supply data is gated behind enterprise pricing; we use proxy signals (job-posting density, government employment statistics) where direct data is unavailable. Per-country reliability varies and we surface confidence flags.
What changes when jobs data updates: data/jobs-by-country.php (resolved per-country record) is rewritten by quarterly cron; per-country-occupation salary-bands recompute; sponsorship-friendliness scores update on visa-rule changes (event-driven, not cron-driven).
When the cron runs: quarterly at 07:00 UTC on the 1st of the quarter for the labour-market sweep. Annual at 07:00 UTC on Jan 1 for the sponsorship-friendliness recalibration. Event-driven for visa-rule-change updates triggered manually.
Where files live: data/jobs-by-country.php (resolved record), data/jobs-occupations-taxonomy.php (the role taxonomy), includes/jobs-template.php (renderer). Hub at /jobs/index.php; per-country pages at /jobs/{country}/.
Why country-comparator not job-board: because real-time job-boards beat us on freshness (we cron quarterly) but lose to us on cross-country comparability. The hub plays the comparison game; localised boards play the listing game. Trying to do both badly is worse than doing one well.
Which renderer: includes/jobs-template.php emits the country-jobs panel + sectoral-demand + salary-bands + sponsorship + visa-pathway + cost-lens cross-links + similar-countries rail. Accepts $country_slug. Echoes directly. Idempotent.
Whose responsibility: data sourcing is on the cron operator + correspondent-contributors. Sponsorship-friendliness scoring is editorial-with-cron-assist. Schema validity enforced by pre-flight. Confidence flags are surfaced explicitly so readers know reliability is uneven across countries.
How to add a new country: (1) declare in jobs-occupations-taxonomy.php which roles to track; (2) source labour-market data from government statistics + proxy signals; (3) populate sponsorship + visa-pathway entries; (4) extend hub render; (5) verify coverage via admin/jobs-coverage.php. Total: about a day per country including sourcing + editorial polish.