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Sample verified profile
This is what your client receives. Open it, no form required.
Candidate 7Q4M
Senior Backend Engineer
9 years experience · San Francisco, CA
Expert-written summary
A senior engineer met the candidate, tested the findings in conversation, and confirmed strong backend fundamentals. Team leadership scope is marked as "Yet to cover".
Evaluation
88%
Strengths
- Designs for failure: idempotency, retries, back-pressure
- Explains trade-offs clearly to non-engineers
- Structures ambiguous problems into testable steps
Weaknesses
- Limited scope leading teams beyond 4 engineers
Yet to Cover
- Team leadership and mentoring approach
- On-call incident handling end-to-end
Supporting Evidence
AI technical interview42 min · recording and transcript
Interviewer: Your retry service starts double-charging under load. Where do you look first?
Candidate: At the idempotency boundary. If the key is generated after the gateway call, every retry looks like a new payment…
Follow-up questions probed lock contention and outbox ordering.
Agentic Collaboration session55 min · work artifacts
Guided an AI agent through a reconciliation refactor. Rejected two unsafe suggestions, added idempotency tests, and explained each decision before accepting the agent's output.
Domain scenario: payment reconciliation20 min · scenario responses
Applied settlement windows and chargeback rules to a realistic month-end mismatch, and identified the missing ledger event behind it.
Expert reviewSenior engineering expert · written summary
A senior engineer met the candidate, tested the findings in conversation, and confirmed strong backend fundamentals. Team leadership scope is marked as "Yet to cover".
How we do it.
Four assessments, then a real expert. Every candidate you receive has been through all of it.
L2 AI Interviewers
Expert-level AI interviewers probe technical skills, reasoning, and practical experience through follow-up questions.
AI Fluency Assessments
Show how well candidates understand AI tools, their limits, and when to trust the output.
Human:AI Collaboration
Agentic Collaboration sessions show how candidates guide AI agents, check their work, and turn it into results.
Behavioral analysis
Interviews reveal how candidates communicate, take ownership, and handle ambiguity.
A real expert meets every candidate.
After the assessments, an expert in the field meets the candidate and writes the summary your client reads.
Verified by Invyte.ai
Every shared profile carries the badge, so your client knows the candidate has been interviewed, assessed, and met by an expert.
In-demand roles we've assessed.
Expertise across the full spectrum of AI and engineering roles.
Company Backgrounds
- +FAANG (Meta, Google, Apple, Amazon, Microsoft)
- +AI-native companies (Anthropic, OpenAI, Mistral)
- +Consulting firms (McKinsey, Boston Consulting, Deloitte)
- +Fast-growing startups (Series A–D funding)
Educational Pedigree
- +Ivy League universities
- +Top-tier tech schools (MIT, Stanford, CMU, Berkeley)
- +International premier institutes (IITs, ETH Zurich, Oxford, Cambridge)
- +PhD programs in ML, AI, Computer Science
Evidence from real interviews.
120,000+
interview minutes
3,000+
candidates evaluated
1,000+
AI fluency scenarios
Your client stays yours.
Client and candidate relationships remain with your firm. Terms are agreed before any candidate is shared.
You decide which candidates to present and which evidence your client can open.
Agreed before anything is shared
- Your client relationships stay with your firm
- Your candidate relationships stay with your firm
- Terms agreed before any candidate is shared
Before you send a role
Send us the role.
We'll send candidates who are already interviewed and human-reviewed, with the evidence attached.
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