Module 03 · Sourcing
Sourcing Context Cheat Sheet — UK / USA
Specialist recruiters win because they know the map: who is growing, who uses which language, where the hiring bar is highest and which pools everyone else ignores. This is that map for startup and tech hiring in the UK and USA.
UK market context
- Main hubs
- London (dominant), Cambridge (deep tech/AI), Manchester, Edinburgh, Bristol
- Notice periods
- 1 month is standard; 3 months common at senior and finance-adjacent companies. Plan offer-to-start of 4–12 weeks.
- Equity expectation
- Options are understood but weighted lightly. Cash matters more than in the US; explain EMI clearly.
- Comp anchors
- Quant and big tech London set the ceiling. Startups compete on ownership, scope and mission, not salary.
- Visas
- Skilled Worker and Global Talent. Sponsorship licence is a genuine sourcing advantage — say so in outreach.
- Talent density signal
- Ex-DeepMind, ex-Improbable, ex-Monzo, ex-Palantir London alumni networks are the strongest referral chains.
USA market context
- Main hubs
- SF Bay Area (AI/infra), NYC (fintech/enterprise), Seattle, Austin, Boston (bio/deep tech)
- Notice periods
- Typically 2 weeks. Processes move fast — slow feedback loses candidates outright.
- Equity expectation
- Sophisticated. Expect questions on strike price, preferred stack, refresh policy and exercise window.
- Comp anchors
- Levels.fyi is the reference point. Big tech and AI labs have reset senior comp expectations sharply upward.
- Visas
- H-1B transfers, O-1 and cap-exempt paths. O-1 is realistic for strong startup and research candidates.
- Talent density signal
- Ex-Stripe, ex-Palantir, ex-Airbnb, ex-OpenAI alumni networks dominate founding-engineer hiring.
Company map
Filter by region, profile and tech stack to build a target-company list for any search. Use these names directly in LinkedIn, Juicebox or GitHub searches.
Region
Profile
Tech stack
46 companies
OpenAI
USAFrontier AI lab, extreme scaling since 2023.
Anthropic
USAFrontier AI lab, research-heavy engineering bar.
Anduril
USADefence tech, hardware + software, aggressive headcount growth.
Palantir
USAFamously selective, strong generalist deployment engineers.
Ramp
USAFintech, one of the fastest revenue ramps in SaaS history.
Stripe
USAPayments infra; a reliable source of strong product engineers.
Databricks
USAData/AI platform at massive scale.
Scale AI
USAData labelling and eval; hires young, very high raw talent.
Figma
USABrowser-based graphics; rare C++/WASM performance engineers.
Vercel
USAFrontend infra; deep TypeScript and Rust tooling talent.
Cloudflare
USAEdge infra; Rust and Go systems engineers at scale.
Jane Street
USAQuant trading; OCaml, extremely high bar, high comp anchor.
Citadel Securities
USAHFT; C++ low-latency specialists, comp benchmark for systems talent.
Deep infra and ML; strong algorithmic screening culture.
Meta
USAScale + performance culture; strong product engineers.
Netflix
USASmall senior teams, top-of-market comp, high autonomy.
Airbnb
USAStrong product and design-adjacent engineers.
Rippling
USACompound HR/fintech product; fast headcount growth.
Deel
USAGlobal payroll; extremely fast international growth.
Perplexity
USAAI search; lean team, very selective.
Cursor / Anysphere
USAAI coding; tiny team, exceptional engineers.
Modal
USAServerless compute for AI; deep Rust/systems work.
Retool
USAInternal tools; strong full-stack TypeScript.
Plaid
USAFintech infra; API-first engineering.
Monzo
UKConsumer bank; microservices, huge Go talent pool.
Revolut
UKFastest-scaling UK fintech; very high performance bar.
Wise
UKCross-border payments; strong JVM and data engineering.
Monolith of quant: XTX Markets
UKLondon quant firm; C++/Python, extreme selectivity and comp.
Optiver / IMC (Amsterdam-London)
UKMarket makers with London desks; C++ low-latency talent.
Improbable
UKHistorically a UK high-bar hirer; strong distributed systems alumni.
DeepMind
UKResearch-grade ML; the UK's strongest AI alumni network.
Synthesia
UKAI video; one of the fastest UK ARR ramps.
ElevenLabs
UKVoice AI; small, exceptionally selective team.
Stability / Faculty / PolyAI
UKUK applied-AI cluster; good source of ML engineers.
Cleo
UKConsumer fintech; strong Python and ML product work.
GoCardless
UKPayments infra; Ruby/Go engineering.
Checkout.com
UKPayments; .NET and Go at scale.
Ocado Technology
UKRobotics + logistics; real-time systems engineers.
Arm
UKSilicon; C/C++ and low-level performance specialists.
Graphcore
UKAI silicon; compilers and C++ systems talent.
Quantexa
UKDecision intelligence; Scala/Spark data engineers.
Multiverse / Beauhurst-tracked scaleups
UKUseful trackers for finding fast-growing UK headcount.
Tessian / Snyk / Darktrace
UKUK security cluster; strong Python/Go security engineers.
Palantir UK (London)
UKLarge London office; selective generalists with commercial exposure.
Isomorphic Labs
UKAI for drug discovery; DeepMind spin-out, very high bar.
Tractable
UKApplied computer vision; strong ML engineering.
Talent pools everyone else overlooks
The obvious pools are the most contested. These are where founders win against better-resourced companies.
Failed / acquired startups
When a startup winds down or is acqui-hired, strong engineers hit the market at once and are rarely contacted by founders. Track shutdown news and LinkedIn 'open to work' spikes at those companies.
Second and third engineers at seed startups
Excellent generalists who joined a company that stalled. They already have zero-to-one experience and are easier to close than big-tech engineers.
Big tech engineers who joined via acquisition
They chose startups once. Filter for anyone whose tenure begins the month their startup was acquired.
Quant / HFT engineers wanting product work
Elite C++ and Python engineers, well paid but often bored. Realistic for infra, performance and data-heavy roles.
Academia and PhD leavers
Especially for ML. Look at recent arXiv authors, PhD students in their final year, and postdocs at UCL, Cambridge, Oxford, Imperial, MIT, Stanford, CMU, Berkeley.
Open source maintainers
The strongest quality signal that exists. Search GitHub by language plus recent activity rather than by job title.
Returners and career-break candidates
Highly capable, far less contested, and often more loyal because fewer companies engaged with them.
Adjacent geographies
UK: Manchester, Edinburgh, Bristol, Cambridge, Dublin. USA: Austin, Denver, Raleigh, Toronto, Seattle. Same skills, less competition, lower comp expectations.
How to turn this into a search
- 1. Pick the profile that matches your role — high growth, high bar, or stack-specific — and take 15–25 target companies from the map.
- 2. Convert them into a Boolean or Juicebox search alongside your title and seniority filters.
- 3. Layer one overlooked pool onto every search so you are never competing only where everyone else is.
- 4. Use the market context above to set expectations on notice periods, comp anchors and equity conversations before you make an offer.
Company lists are directional market context, not a live database — headcount, stacks and hiring bars move. Re-check anything before you build a search around it.