What conducting a panel interview actually requires
A panel interview brings multiple interviewers together to evaluate one candidate at the same time. For technical hiring, this usually means a mix of the hiring manager, a senior engineer, and sometimes a cross-functional partner, all in the same conversation. Done well, it replaces three separate one-on-one interviews with a single, more efficient conversation and gives you multiple independent perspectives on the same answers. Done poorly, it turns into a disorganized group interrogation that stresses out candidates and produces conflicting feedback nobody can act on.
Here is how to conduct a panel interview that actually produces a clear hiring decision, in five steps: define what the panel is evaluating, assemble panelists with distinct roles, build a shared script and rubric, run the interview with a clear agenda, then score independently before the panel debriefs.
Step 1: Define what the panel is evaluating
Before you pick panelists or write questions, decide what the interview needs to measure. For a technical role, that typically breaks into three or four competencies: core technical skill, system-level thinking, collaboration and communication, and role-specific domain knowledge, such as data pipeline experience for an ML engineer or frontend architecture for a senior web developer.
Write these competencies down and share them with every panelist in advance. Without an agreed list, panelists default to evaluating whatever they personally value, and two interviewers can walk away with completely different impressions of the same candidate. Google’s own structured interviewing research found the same pattern at scale — interviews built around a shared, agreed set of criteria produce more consistent, less biased hiring decisions than freeform conversations.
Step 2: Assemble the right panelists and assign roles
Most technical panels work best with three to five interviewers. More than that, and the interview becomes hard to schedule and overwhelming for the candidate. Each panelist should own a distinct slice of the evaluation rather than duplicating the same questions: the hiring manager leads the conversation and covers role expectations and career goals, a senior or staff engineer owns technical depth and live coding or system design, a peer or cross-functional partner assesses collaboration and communication, and an HR or recruiting partner, where the team includes one, keeps the process consistent and compliant across candidates.
Assign these roles before the interview, not during it. Every panelist should also know which questions to avoid entirely: anything touching age, family status, religion, disability, or national origin has no place in a technical evaluation and creates real legal exposure.
Step 3: Build a structured script and scoring rubric
A structured interview asks every candidate the same core questions in roughly the same order, which is what makes candidates comparable at the end of the process. Build a shared script with a fixed set of questions per competency, mapping each question to the panelist who owns it, a simple one-to-five rating scale with a short description of what a 1, a 3, and a 5 answer looks like for each question, and space for the panelist’s own notes, separate from the score. Share the job description, the candidate’s resume, and the rubric with every panelist before the interview, not five minutes beforehand. For a deeper library of example questions across Python, ML, and general CS roles, see our technical interview questions guide.
A rubric only works if panelists can look at an answer and immediately place it on the scale. Take a system-design question for an ML engineering candidate, such as “walk me through how you’d debug a model that performs well in training but poorly in production.” A score of 1 looks like naming one generic cause, such as overfitting, with no investigation process at all. A score of 3 looks like checking for data drift and retraining, but not ruling out other causes systematically. A score of 5 looks like walking through a structured process: checking for data or label drift, validating the training and serving pipeline for skew, reviewing feature distributions, and explaining how to isolate the cause before acting.
Build a similar scale for every question in the script, and calibrate as a panel beforehand by walking through a sample answer together and agreeing on where it would score. Skipping this step is why two panelists using the “same” rubric can still land on very different numbers.
Step 4: Run the interview with a clear agenda
Open by introducing every panelist and their role, and briefly explain the format: how long the interview will run, how many questions each person will ask, and when there will be time for the candidate’s own questions. This alone reduces candidate anxiety and produces better answers, because the candidate isn’t guessing what’s coming next.
During the interview, keep to one person asking a question at a time — a free-for-all where panelists jump in with follow-ups from different angles overwhelms the candidate and makes it hard to compare notes afterward. Move through one competency block at a time rather than jumping between technical and behavioral questions, and leave room for follow-up questions within each panelist’s block so they can probe a shallow or unclear answer without drifting off topic. Each panelist should also take individual notes rather than relying on a single note-taker, since a shared note-taker’s phrasing can unintentionally anchor everyone else’s opinion.
A typical technical panel interview runs 45 to 90 minutes total, and that time divides roughly evenly across competency blocks. Reserve the last 5 to 10 minutes for the candidate’s own questions. Going much longer than 90 minutes tends to produce fatigue on both sides of the table and doesn’t meaningfully improve signal quality.
Running a panel interview remotely
Most technical panels now run at least partly over video, especially for distributed engineering teams, and a remote panel needs a few extra rules on top of the ones above. Keep every panelist’s microphone muted except the one currently speaking, since overlapping audio is far more disruptive on a call than in a room. Assign one panelist to drive the shared document or coding environment during any live-coding portion, so the candidate isn’t watching multiple cursors move at once. And keep cameras on: a candidate facing four black video tiles has a much harder time reading the room than one facing four visible interviewers.
Step 5: Score independently, then debrief
The most common mistake in panel interviewing happens after the candidate leaves the room: the panel jumps straight into open discussion, and the most senior or most vocal interviewer’s opinion ends up dominating everyone else’s assessment.
Instead, have every panelist submit their scores and notes independently before any group discussion happens. Only after that should the panel meet, ideally within 24 hours while the interview is still fresh, to compare scores, discuss disagreements, and reach a decision. If two panelists scored the same answer very differently, that’s worth discussing directly rather than averaging away.
Common panel interview mistakes to avoid
Too many panelists is one of the most common issues: beyond five or six people, the interview becomes exhausting for the candidate and hard to synthesize afterward. No assigned ownership is another, since if every panelist can ask about anything, competencies get double-covered and others get skipped entirely. Skipping the calibration conversation causes inconsistent scoring, even with the same rubric in hand, because panelists who have never discussed what a strong answer looks like will interpret the scale differently. Group discussion before individual scoring is the single biggest source of bias in panel interviews, since it lets one strong opinion move everyone else’s assessment. And no structure shared with the candidate means candidates spend the first ten minutes trying to figure out who’s asking what, instead of giving their best answers.
Where automated technical screening fits into the process
For technical and engineering roles specifically, many hiring teams now run an automated coding assessment or AI-driven technical screen before the panel stage, rather than using panel time to test baseline coding ability. Codeaid’s AI Interviewer, for example, generates domain-specific coding assessments — covering areas like traditional software engineering, machine learning, and generative AI — and scores them automatically before a candidate ever reaches a live interview.
That approach frees up the panel to spend its time on the things a panel is actually good at assessing: system design reasoning, collaboration, and how a candidate communicates trade-offs out loud, rather than re-verifying whether they can write working code. The technical screen and the panel interview end up complementing each other instead of covering the same ground twice.
FAQs
How can I conduct technical interviews for coding positions effectively?
Separate the two jobs a technical interview process has to do. Use an automated coding assessment to verify baseline technical ability before anyone’s calendar gets involved, then reserve the panel interview for what a live conversation is actually good at: system design reasoning, debugging thought process, and how a candidate communicates trade-offs. Running both, in that order, with a shared rubric across panelists, is the most effective structure for technical hiring.
How should you structure your technical interview panel process?
Start by defining the competencies the panel needs to evaluate, assign each competency to a specific panelist, build a shared script and rubric, and score independently before any group discussion. Structure is what makes panel interviews fair and comparable across candidates — without it, panel interviews tend to produce noise rather than a clear signal.
How many people should be on an interview panel?
Three to five is the practical range for most technical roles. Fewer than that loses the benefit of multiple perspectives; more than that becomes hard to schedule and overwhelming for the candidate.
Should the whole panel discuss the candidate together before scoring?
No. Each panelist should score independently first. Group discussion before individual scoring is one of the most common ways panel interviews end up biased toward whoever speaks first or most confidently.
Can panel interviews replace a technical coding test?
They can, but they don’t need to. Many teams run an automated coding assessment first to verify baseline technical ability, then use the panel interview for system design, collaboration, and communication — where a live conversation adds more value than a scored test.