01
Case study / Eightfold AI
AI
Interviewer
An enterprise interview system designed to expand access without removing human judgment from the hiring decision.
Company
Eightfold AIRole
Director, UX DesignDuration
2025–ongoingScope
Enterprise hiring01 / Leadership scope
I led the product experience, from strategic premise to the moments people rely on.
As Director of UX Design, I set the experience direction for AI Interviewer and led a multi-disciplinary design team across the recruiter and candidate journeys. My remit was to turn an ambitious AI capability into a product that hiring teams could understand, control, and adopt.
02
Led the system design
Shaped the connected recruiter and candidate journeys, core interaction patterns, and workflows that made the product usable at enterprise scale.03
Made trust actionable
Defined the trust model across evidence, human review, integrity signals, and deployment so adoption was built into the experience.02 / The product decision
Scale access without outsourcing judgment.
Hiring teams are expected to screen more candidates, move faster, and maintain a consistent bar—often with the same team. The conventional first screen makes recruiter capacity the bottleneck, leaving strong applicants waiting or unseen.
The pivotal experience decision was not to automate a recruiter’s judgment. It was to make a high-quality, role-aware first interview available to more people, then return a transparent record a recruiter could interrogate and act on. That decision set the bar for every subsequent workflow, interaction, and trust safeguard.
03 / Design strategy
Scale the interview,
not the uncertainty.
I used one design rule to resolve the central trade-off: every AI interaction had to create evidence a recruiter could understand, question, and use—not a black-box recommendation to accept.
Decision 01 / Ground the AI
Start with the role, not a generic script.
- Role and skill criteria
- Interview guides and question sets
- Custom hiring requirements
Decision 02 / Keep people accountable
Return evidence, not an unexplained verdict.
- Structured transcripts and scorecards
- Competency-level signals
- Human review and follow-up
04 / Decisions in the product
Make the role the source of truth
I shaped a system that connects interview guides, skills, and evaluation criteria to the role itself. A centrally managed interview library gives teams stronger defaults while preserving the flexibility their hiring context requires.
Let the conversation adapt, not drift
I led the interaction direction for natural, multi-turn interviewing: role-specific follow-ups that respond to a candidate’s answer and assess demonstrated reasoning, rather than simply collecting responses to a fixed script.
Design the output for a decision meeting
I made the structured hiring record—not a single score—the product outcome: transcript, scorecard, competency evidence, and a clear path back to the interview. Recruiters can review the rationale, not just receive a result.
05 / One system, many interview moments
A common standard across every way a candidate can show what they know.
01
Profile screening
Assess fit, interest, and role requirements through an always-on interview experience.02
Functional interviews
Explore problem-solving, communication, leadership, and role-specific competency through scenarios and case studies.03
Coding & whiteboarding
Evaluate the reasoning behind a solution with adaptive technical follow-ups—not only its final output.04
Language fluency
Bring CEFR-based language assessment into the interview so global teams can evaluate consistently.06 / Designed for adoption, not novelty
Enterprise trust is a product experience.
I treated fairness, privacy, integrity, and fit with existing systems as product constraints—not an implementation checklist. The experience had to make those constraints visible and usable for the people accountable for hiring.
Human oversight
AI supports the process; recruiters retain the context and authority to review, decide, and handle exceptions.
Integrity by design
Identity verification and reviewable interview-integrity signals help teams establish confidence at scale.
Built into the workflow
Flexible deployment paths—from ATS-connected hiring stages to standalone use—made the system practical to adopt.
07 / What this enables
More access. Better evidence. Less manual drag.
faster time to fill in the product’s target hiring workflow.
to complete an interview in production results shared with the field.
languages supported for consistent, global interview delivery.
interview-integrity signals available to help recruiters review suspicious activity.
08 / In motion
See AI Interviewer in action.
From setting the brief to making a confident decision, these product moments show how AI Interviewer keeps every step of hiring clear, human, and in motion.
01 / Recruiter experience
From requisition to interview-ready02 / Candidate experience
A guided, candidate-first interview09 / Outcomes in use
A faster path to a confident decision.
AI interview invites sent across enterprise hiring pipelines.
saved per recruiter, per week through streamlined screening and evaluation.
completion rate for graduated automation workflows in live deployments.
candidate satisfaction across more than 31,000 completed screening sessions.
My role
I set the experience strategy, led the design team, and stayed hands-on across the workflows that carried the strategy into the product. The result was an AI interview experience designed to increase capacity while leaving hiring teams with context, control, and accountability.
Confidentiality
A note on the work shown.
This case study shares a high-level view of confidential work completed under NDA. Detailed flows, product screens, research, and further outcomes are not displayed here.
If you’d like to explore the work in more detail, please get in touch to arrange a conversation.
Next project
Interview Feedback ↗