Blockchain, digital asset and AI teams compete for a small pool of people with hands-on experience. Titles change from one company to the next, résumés are full of the same keywords, and the gap between “has experimented with” and “has shipped and maintained” is large. A disciplined hiring process makes the difference.

Start with the problem, not the buzzword

Before writing a job description, write down what this person will own in their first six months. “Blockchain engineer” could mean someone who maintains node infrastructure, someone who writes and audits smart contracts, or someone who integrates custody APIs into a banking platform. “AI engineer” ranges from research-minded model builders to product engineers who wire large language models into existing applications.

Ask three questions:

  • What will they build or run? For example a Bitcoin payment integration, a Solidity protocol, a retrieval-augmented support assistant or a fraud model.
  • What will they inherit? Existing code, vendors, compliance obligations and on-call duties all shape the profile.
  • Who will they work with? Security, compliance, finance and product partners matter as much as the technical stack.

Look for evidence, not vocabulary

In emerging fields, keyword matching fails. Strong candidates can usually show you something:

  • Public work. Open-source contributions, audited contracts, technical write-ups or conference talks.
  • Production stories. Ask about an incident, such as a failed deployment, a model that drifted or a gas-cost surprise, and how they handled it.
  • Security instincts. For digital asset roles, listen for how candidates think about key management, access controls and adversarial behavior. For AI roles, listen for evaluation, data quality and guardrails.

Technical exercises should mirror the real job. A short paid exercise or a structured design conversation often reveals more than an abstract coding puzzle.

Don’t overlook the “adjacent” talent

Some of the best hires come from neighboring disciplines: payments engineers who understand settlement, security engineers who move into protocol work, data engineers who move into machine learning operations, or compliance professionals from traditional finance who learn digital asset rules. Pair them with experienced specialists and they can ramp up quickly.

Compliance and governance roles are part of the team

Digital asset businesses need AML, KYC, sanctions and accounting expertise as much as engineering. AI programs increasingly need governance specialists who can document models, assess risk and work with legal. Plan these roles early instead of treating them as an afterthought.

Move quickly, but verify

Experienced candidates in these fields often weigh several options at once. Keep your process to a small number of focused steps, share feedback promptly, and be ready to explain the long-term roadmap. At the same time, verify claims: check references, confirm contributions and, where relevant, run background checks.

Consider flexible models

If you are not sure what the long-term role looks like, a contract or contract-to-hire engagement lets you bring in expertise for a pilot, audit or launch and decide on permanent headcount with better information.

Building a blockchain, digital asset or AI team? Our Blockchain, Digital Assets & AI recruiters can help you define the role and find people who have done the work. Talk to us.