Configure the role
Define competencies, targeted questions, must-haves, and scoring guidance that reflect success in the specific role.
Structured video interviews for high-stakes technical hiring
Hire AI talent with
evidence, not impressions.
HiringMirror helps enterprise talent teams screen AI engineers and technical candidates against the capabilities that matter in production—then gives hiring managers an explainable shortlist before they invest live interview time.
Role-specific rubrics · Evidence-linked evaluation · Candidate-friendly experience · Human decisions stay human
Structured video screening
Targeted AI talent evaluation
Explainable scorecards
Same rubric for every candidate
Human review stays essential
Structured video screening
Targeted AI talent evaluation
Explainable scorecards
Same rubric for every candidate
Human review stays essential
60 seconds, no login required
Watch the mirror
do its work.
A candidate ships a fix an AI assistant suggested. HiringMirror watches whether they caught what was wrong with it. That's the difference between reviewing answers and reviewing judgment.
- AI Co-Pilot Stress Test surfaces a hallucination mid-interview
- Candidate vs. AI Replay shows exactly what got kept and why
- Every scorecard ships with a shareable Proof-of-Work video card
From video interview to interview-ready shortlist
Stop reviewing interviews.
Start reviewing evidence.
HiringMirror converts first-round conversations into structured, comparable signals—so recruiters and technical leaders can spend their time on candidates with the strongest evidence of fit.
Run structured screens
Candidates complete a consistent, branded video interview on their own time, with no repetitive first-round scheduling burden.
Review the evidence
Compare candidates through scorecards, answer-level observations, timestamps, and plain-language rationale for each recommendation.
Curated Domain Intelligence
Industry Vertical Templates
Specialized interview blueprints designed by domain experts. Select a vertical to view calibrated questions for technical and leadership assessments.
Vertical 02
Banking & Financial Services
Risk, regulation, and high-stakes transaction workflows.
01
Describe your experience working on a banking or financial-services product and explain the key business processes involved.
02
Tell us about a financial transaction, payment, lending, or banking workflow you have worked with. What were the critical controls and risks?
03
Describe a situation where you had to balance customer experience with regulatory, security, fraud, or risk requirements.
Apply Template →
Meet Todd
Your screening operations agent,
not your hiring decision-maker.
Todd handles repetitive early-stage recruiting work: candidate outreach, interview invitations, reminders, structured screening workflows, and scheduling.
Your team sets the role criteria, owns the rubric, reviews the evidence, and makes every final hiring decision.
Meet Todd in a demoOne place to review every first round
A shortlist your technical leaders can understand.
- Role-specific interview prompts and evaluation criteria
- Candidate comparison grounded in observable, job-relevant behavior
- Answer-level evidence and timestamps behind each score
- Clear advance, review, and hold recommendations
- Structured records for faster hiring-manager calibration
Purpose-built for AI and engineering hiring
Go beyond “tell me about your stack.”
See how AI talent thinks.
HiringMirror gives talent teams a structured way to screen AI engineers, machine-learning engineers, data scientists, platform engineers, and technical product talent before consuming scarce technical interview time.
Role-specific technical prompts
Create targeted questions for LLM applications, retrieval systems, model evaluation, MLOps, data pipelines, inference trade-offs, and production reliability.
Evidence of engineering judgment
Review how candidates reason about quality, latency, cost, privacy, safety, observability, and maintainability—not just whether they repeat familiar AI terminology.
Consistent first-round signal
Give every candidate the same role-relevant prompts and evaluation criteria so technical leaders begin deeper interviews with a more comparable baseline.
Better use of expert time
Reserve live engineering interviews for architecture, collaboration, and complex problem solving instead of repeated introductory screening conversations.
Example: Applied AI Engineer rubric
Evaluate the capabilities that matter in production.
Problem framing
Turns an ambiguous business problem into measurable technical requirements.
Model and system judgment
Explains model selection, retrieval, prompting, fine-tuning, and failure modes.
Production readiness
Addresses testing, monitoring, evaluation, cost, latency, and reliability.
Responsible AI awareness
Recognises privacy, security, safety, bias, and governance considerations.
What sets the screen apart
Built for a workplace
where everyone uses AI.
Generic screening tools ask candidates to answer questions. HiringMirror watches how they think, verify, and communicate when an AI assistant is already in the room—because it already is, in the job.
AI Co-Pilot Stress Test
A controlled AI assistant joins the interview and offers a plausible, flawed suggestion. We watch whether the candidate catches it—or ships it.
Candidate vs. AI Replay
Side-by-side evidence of what the AI proposed and what the candidate actually shipped.
Executive Zoom-Out
One adaptive follow-up after every answer—"what larger system does this affect?"—scored on whether a candidate moves from task to business thinking.
Proof-of-Work video card
A shareable summary hiring managers and candidates can both trust.
Evidence-backed benchmark levels
Every candidate lands on a level your team already agrees on the meaning of.
Governance, by default
Guardrails your legal and DEI stakeholders can sign off on.
0x
Faster time-to-shortlist for technical roles
0%
Fewer live interviews spent on early screening
0h
Typical turnaround for a completed pipeline
0%
Hiring managers who trust the shortlist they receive
Built for fairer, more defensible hiring
Every recommendation has
a reason attached.
HiringMirror is designed to make assessment criteria visible, evaluation more consistent, and human review more informed.
Observable behaviors
Review what candidates communicate and how they structure relevant answers—not broad personality labels or opaque impressions.
Explainable by default
Scores are accompanied by answer-level interview evidence and clear rationale your recruiting and hiring teams can inspect.
Consistent criteria
Candidates interviewing for the same role are assessed against the same job-relevant rubric and prompt set.
Human control
HiringMirror supports screening and review; people remain responsible for every hiring decision.
The other side of the mirror
Candidates can practise against
the same standards.
Instead of guessing what “a strong interview” means, candidates can receive observable feedback, work on one practical improvement, and arrive better prepared for a structured conversation.
Candidate Mirror report
Clarity: 8.2 / 10
“You opened most answers with a concise summary and used a clear situation-action-result structure in four of five examples.”
- Feedback linked to specific interview moments
- One focused, practical practice target
- Clearer expectations before the real interview
From talent teams already screening this way
What changes
once evidence leads.
"Our engineering leads used to sit through screens that told us almost nothing about production judgment. Now they open a scorecard and know exactly where to dig deeper."
HT
Head of Talent
AI-native fintech startup
"The AI Co-Pilot Stress Test told us more in twelve minutes than three rounds of behavioral questions ever did. It's the closest thing to watching someone actually work."
VP
VP Engineering
Applied ML platform
"Candidates stopped complaining about black-box rejections. Everyone can see the same rubric, and that alone changed how our recruiters defend a decision."
DR
Director, Talent Acquisition
Enterprise data platform
Before you book a demo
Questions we get
from talent leaders.
Does HiringMirror replace live technical interviews?
No. It's a structured first-round screen. Live interviews stay focused on architecture, collaboration, and deeper problem solving—HiringMirror just makes sure the candidates who reach them are worth that time.
Who actually makes the hiring decision?
Your team, always. HiringMirror surfaces evidence, observable behavior, and a recommendation—advance, review, or hold. A person reviews the scorecard and owns every outcome.
Can we customize the rubric for a specific role?
Yes. Competencies, prompts, must-haves, and scoring guidance are configurable per role, from applied AI engineer to platform and data science positions.
What do candidates actually experience?
A single structured video interview they complete on their own schedule, followed by a Candidate Mirror report with observable feedback—so even candidates who don't advance leave with something useful.
How is this different from AI-scored interview tools?
Most tools score whether an answer sounds right. HiringMirror is built around verification and judgment—including a live AI Co-Pilot Stress Test—so you're evaluating how a candidate works with AI, not just what they say about it.
Make your next technical shortlist easier to trust
Bring better evidence into every AI hiring decision.
Give technical leaders a clearer first-round signal, give candidates a more consistent experience, and give your talent team time back.
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