How to evaluate technical candidates as a non-engineer

A non-engineer evaluates technical candidates by asking qualitative, situational questions about real decisions, setting a deliberate policy on AI use during assessments, and using reference checks, including additional non-technical references, to learn how the engineer actually works with a team.

The instinct is to borrow a coding test and hope the score means something. It rarely does in your hands, because you cannot interpret it. The better move is to evaluate the dimensions you genuinely can read, and there are more of them than most non-technical managers assume.

Ask Situational Questions You Can Actually Judge

Skip trivia about syntax and ask about decisions. Have the candidate walk you through a real problem they owned: what the situation was, the options they weighed, what they chose, and why. Then ask them to explain their decision-making process out loud. You are not grading the code, you are evaluating how they think, whether they can make trade-offs explicit, and whether they can explain a complex choice to someone who is not an engineer, which is a core job skill in itself.

Good engineers get clearer as they go deeper. A weak or embellished candidate gets vaguer, leaning on buzzwords where a real decision-maker would give specifics. You can hear that difference without reading a line of code.

Ask About Quality, Reliability, and Incident Response

Three topics reveal seniority to any listener, because the answers are about behavior, not syntax:

• Quality. How do they decide something is good enough to ship? What does "done" mean to them, and how do they prevent the same bug twice?
• Designing for reliability and uptime. How do they build something that keeps working when traffic spikes or a dependency fails? Do they think about failure before it happens?
• Incident response. Walk me through the last time something broke in production. What did you do first, how did you communicate, and what changed afterward?

A candidate who answers these with calm, specific stories is showing you the exact maturity that keeps systems, and teams, from falling over. Vague or defensive answers here are a louder signal than any whiteboard stumble.

Decide Your AI Policy, Deliberately

Before the assessment, decide whether candidates may use AI, and do it on purpose rather than by default. AI-assisted cheating in technical assessments is now pervasive; assuming it is not happening is simply the least informed choice. There is a strong case for the opposite stance: if your company builds with AI tools every day, allowing them in the assessment and watching how the candidate prompts, reviews, and corrects the output tells you how they will actually work on your team. The skill worth testing has shifted from "can you write this unaided" to "can you direct and verify a tool you will use on the job."

Use References, Especially Non-Technical Ones

References are where a non-engineer has the most leverage, so do not waste them confirming dates. Ask for additional non-technical references, a former product manager, designer, or support lead, and ask how the engineer interfaces with multidisciplinary teams. Do they explain technical constraints without condescension? Do they push back usefully, or just resist? Are they reliable when a release is on the line?

An engineer can impress in an interview and still be hard to work with. The people who sat next to them know which, and non-technical references will tell you things a peer code reviewer never would.

One Thing Interviews Can't Confirm: Who They Are

All of this assumes the person you evaluate is the person you hire. In remote engineering hiring that is not safe to assume, proxy interviews and stolen identities are real. Skill assessment and identity verification are different jobs; see how to detect fake candidates in remote software engineering. PinpointVerify handles the second: an in-person ID check by a state-licensed notary confirms the engineer you assessed is the one who shows up, so your evaluation actually means something.