Author: Zackary Skelly (Head of Talent at Dragonfly)
Compiled by: Deep Tide TechFlow
Deep Tide Introduction: Dragonfly releases the 2026 crypto industry insights report, revealing a fundamental shift in hiring logic. In 2025, the industry saw a net reduction of 472 people, but compliance roles surged by 340%, and data science roles grew by 74%. The most critical change: candidates are no longer impulsive about the bull market; they want clear value explanations and certainty. If you can't explain "why this role is important," the conversion rate will plummet.
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We are now in the first quarter of 2026, and the hiring situation in the cryptocurrency space is completely different from any previous cycle.
We have just released the latest "Talent Insights Report," detailing how we got here and what it means for founders and talent teams.
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TL;DR
2025 did not kill crypto hiring; it matured it.
Companies are no longer hiring based on price but on actual needs.
This shift has become the new benchmark heading into 2026.
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The year was clearly divided into two halves.
The first half of 2025 (25H1) was turbulent, with pro-crypto optimism quickly reversing amid macro shocks.
Job removals surged in March (750), with most losses concentrated in the first half.
Approximately 3,700 new jobs were added for the year, while about 4,100 were removed, resulting in a net reduction of -472.
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The second half (H2) brought discipline and recovery.
The overall job trend in H2 was largely consistent with 2024, just at a lower overall level.
July reset, August bottomed out, September reopened, and Q4 stabilized.
The more severe reset in spring was the main reason 2025 overall was lower than 2024.
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In our 25H1 report, we made some predictions. Let's score them now:
✓ Late Q3 rebound (September job openings +26%), Q4 slowdown, compliance hiring started early
✗ Underestimated the degree of divergence in traffic and applications; overestimated the resilience of legal roles relative to compliance roles
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The real shift from 25H1 to H2 was not how many people companies hired, but what roles they hired for. Core first, earn the right to scale.
→ Engineering: -12%, still the anchor → Marketing: -27% → Design: -33% → Customer Service: -35% → Sales & BD: -16% → Legal: -41% → Compliance: +340%
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Data science was the clearest winner of the year, up +74% year-over-year. (Thanks to AI?)
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Interesting changes also happened on the candidate side.
Traffic remained stable in the second half, while applications dropped by about 26%.
People are still browsing, just not submitting applications as easily.
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In early cycles, market excitement did most of the hiring work: rising salaries, influx of applications.
This mechanism is failing.
Stronger months still drive page views, but attention conversion rates are not what they used to be.
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Why? Partly because candidates have become more cautious.
They are more rigorously screening companies for durability, ownership clarity, team quality, and technical credibility: open-source proof, product depth, hardcore problems, GTM roadmap.
Generic category narratives no longer work.
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Areas of concentrated belief: Infrastructure, DeFi, L1, and L2 remain core, but DeFi interest has narrowed to stablecoins, payments, and RWA.
Fintech-related and institutional use cases have gained significant attention. AI remains a key interest point.
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Stage preferences also tell an interesting story.
Seed and Series A stages are still the most attractive to candidates, with high demand for founder roles and first-employee roles. However, larger, more mature companies can still attract interest.
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The most common factor causing candidates to drop out is not compensation, stage, or size, but ambiguity.
If you cannot clearly explain why the company is important, what specific scope they will own, and why the opportunity has lasting power, the conversion rate will drop significantly.
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Geographically, remote work is still the norm, but the most active hiring teams are more concentrated in New York and lean towards in-person work.
Talent remains global, but New York + the Bay Area still dominate. Europe is the largest non-US hub.
(Note: Specific geographic hiring = smaller TAM, longer hiring cycles.)
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Another factor shaping the current landscape: Hiring is concentrating towards later-stage teams and significantly in the verticals candidates are most interested in.
We expect hiring for the remainder of 2026 to be driven more by acquisitions, pivots, and consolidation, rather than pure new growth.
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So what should founders do?
Hire based on milestones—product launches, revenue, partnerships, regulatory progress—not market cycles or calendar plans.
Companies that did well with hiring in H2 2025 could clearly articulate and stick to the reason for each role's existence.
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Know that teams are different, so sequence hires thoughtfully:
→ Core builders first (engineering, security, data/protocol) → BD explores fit → Product is flexible based on type (consumer earlier, infrastructure leaner) → Compliance, finance, risk → Marketing/support scales after leverage appears
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Keep pipelines always open for scarce talent.
Engineering, AI/ML, and security roles are severely supply-constrained and cannot be restarted from zero every cycle. Even if specific needs are closed, relationships should be kept warm.
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Recognize that the way roles are sold has changed.
Candidates want runway clarity, clear ownership for the first 30–60 days, and transparent upside mechanisms.
You must sell differentiation. You are not selling your category; you are selling why you will win and what specific role they can play.
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You also need a real AI story. Not "we are an AI company."
Candidates want to know:
→ How AI is used internally → How it changes the product → Whether it creates a real advantage
Vague answers lose talent.
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Specific advice for talent teams:
Put your strongest people at the front of the process (first impressions matter), keep interview loops tight, and provide clear feedback.
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An open question: AI makes 2026 harder to predict.
People can do more with fewer people. Better tools enable some to start their own. Some might go work directly on AI.
Meanwhile, higher output per employee means faster scaling, and crypto is positioned more broadly than ever.
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Our current view on AI's impact: Before clear AI × Crypto use cases solidify, deceleration signals are stronger than acceleration signals.
📎 Further reading: The Agentic Economy Will Be Massive, Agentic Commerce Won't
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Our baseline expectation for 2026: Flat to moderate growth, led by engineering, AI/data, and security. Consolidation will continue.
Whether bull, baseline, or bear market, this is a year focused on quality building.
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The teams that will win talent will be those with the most credible stories, not the loudest ones.
Execution discipline, durable business models, and good explanations of both are essential.
