Project detail
Project detail
Project detail
Candidate Matching
Candidate Matching
Candidate Matching
AI-assisted candidate matching that surfaces best-fit talent in seconds while keeping recruiters in control.
Problem
Problem
Hiring teams face hundreds of applications per role.
Evaluating candidates manually is slow, inconsistent, and biased toward surface-level signals.
As volume increases, decision quality drops — not because of lack of talent, but because humans are overwhelmed.
Hiring teams face hundreds of applications per role.
Evaluating candidates manually is slow, inconsistent, and biased toward surface-level signals.
As volume increases, decision quality drops — not because of lack of talent, but because humans are overwhelmed.
Hiring teams face hundreds of applications per role.
Evaluating candidates manually is slow, inconsistent, and biased toward surface-level signals.
As volume increases, decision quality drops — not because of lack of talent, but because humans are overwhelmed.
Key tension
Key tension
Speed is needed, but blind automation erodes trust.
Speed is needed, but blind automation erodes trust.
Speed is needed, but blind automation erodes trust.
Process
Process
Process
Research & Behavioral Insights
Research & Behavioral Insights
Through observation and feedback from hiring managers and recruiters, three consistent behavioral patterns emerged:
Through observation and feedback from hiring managers and recruiters, three consistent behavioral patterns emerged:
User Research – Key Behavioral Patterns
User Research – Key Behavioral Patterns
Through interviews and observation, three dominant behavior patterns emerged:
Through interviews and observation, three dominant behavior patterns emerged:
Through interviews and observation, three dominant behavior patterns emerged:
Signal overload
Recruiters review large volumes of candidates under time pressure. As a result, evaluation becomes shallow and order-biased rather than merit-based.
Signal overload
Recruiters review large volumes of candidates under time pressure. As a result, evaluation becomes shallow and order-biased rather than merit-based.
Trust hesitation
Recruiters are open to AI assistance, but trust depends on understanding how recommendations are made.
Trust hesitation
Recruiters are open to AI assistance, but trust depends on understanding how recommendations are made.
Trust hesitation
Recruiters are open to AI assistance, but trust depends on understanding how recommendations are made.
Fear of mistakes
Hiring decisions feel high-risk. When automation is opaque, recruiters default to familiar signals to reduce perceived risk.
Fear of mistakes
Hiring decisions feel high-risk. When automation is opaque, recruiters default to familiar signals to reduce perceived risk.
Fear of mistakes
Hiring decisions feel high-risk. When automation is opaque, recruiters default to familiar signals to reduce perceived risk.
Key Insight
AI should support judgment — not replace it.
Effective matching must be assistive, explainable, and correctable, allowing humans to stay confident and in control.
AI should support judgment — not replace it.
Effective matching must be assistive, explainable, and correctable, allowing humans to stay confident and in control.
AI should support judgment — not replace it.
Effective matching must be assistive, explainable, and correctable, allowing humans to stay confident and in control.
AI Matching Model
AI Matching Model
The matching system evaluates candidates using a combination of structured and inferred signals:
The matching system evaluates candidates using a combination of structured and inferred signals:
Role requirements skills, experience, availability
Role requirements skills, experience, availability
Candidate profile data resume, answers, history
Candidate profile data resume, answers, history
Contextual relevance job-specific priorities
Contextual relevance job-specific priorities
Confidence weighting strength vs uncertainty of signals
Confidence weighting strength vs uncertainty of signals
AI generates ranked recommendations, not decisions.
Humans always make the final call.
AI generates ranked recommendations, not decisions.
Humans always make the final call.
Designing Trust in AI Decisions
Designing Trust in AI Decisions
Candidate Matching was designed around a core principle:
AI should assist hiring decisions without becoming a black box.
Trust was built through transparency, control, and clarity — not blind automation.
Candidate Matching was designed around a core principle:
AI should assist hiring decisions without becoming a black box.
Trust was built through transparency, control, and clarity — not blind automation.
AI Candidate Insights
System behavior
For each candidate, AI generates contextual insights explaining suitability for the role — highlighting relevant skills, experience, availability, and other role-specific criteria.
For each candidate, AI generates contextual insights explaining suitability for the role — highlighting relevant skills, experience, availability, and other role-specific criteria.
How it appears in the UI
Recruiters can interact with an AI chat per candidate to ask follow-up questions and understand why someone is a strong fit. Explanations are concise, grounded in real signals, and easy to verify.
This reduces guesswork and builds confidence in shortlisting decisions.
Recruiters can interact with an AI chat per candidate to ask follow-up questions and understand why someone is a strong fit. Explanations are concise, grounded in real signals, and easy to verify.
This reduces guesswork and builds confidence in shortlisting decisions.
Conversational Search
System behavior
The system interprets natural language queries and refines results incrementally, adapting to recruiter intent instead of forcing complex filters upfront.
The system interprets natural language queries and refines results incrementally, adapting to recruiter intent instead of forcing complex filters upfront.
How it appears in the UI
Recruiters search through conversation — typing queries naturally and narrowing results step by step. This simplifies complex searches and makes finding relevant candidates faster and more intuitive.
Recruiters search through conversation — typing queries naturally and narrowing results step by step. This simplifies complex searches and makes finding relevant candidates faster and more intuitive.
Customizable Ranking
System behavior
AI rankings are adjustable based on recruiter priorities such as experience, availability, certifications, or role-specific skills.
AI rankings are adjustable based on recruiter priorities such as experience, availability, certifications, or role-specific skills.
How it appears in the UI
Recruiters can tune ranking criteria directly, reshaping the shortlist in real time. AI adapts instantly, but never locks outcomes.
This ensures results align with business needs while maintaining transparency and control.
Recruiters can tune ranking criteria directly, reshaping the shortlist in real time. AI adapts instantly, but never locks outcomes.
This ensures results align with business needs while maintaining transparency and control.
Human-in-the-Loop by Design
Across all interactions:
AI explains recommendations
Confidence and uncertainty are visible
Recruiters can override decisions at any point
AI remains adaptive — but accountable. Humans always make the final call.
Across all interactions:
AI explains recommendations
Confidence and uncertainty are visible
Recruiters can override decisions at any point
AI remains adaptive — but accountable. Humans always make the final call.
Impact
Impact
Impact
Impact & Outcomes
Impact & Outcomes
Design
Design
Design
Design System & Brand Expression
Design System & Brand Expression
Alongside interaction design, I was responsible for shaping the visual language and component system to ensure consistency, clarity, and scalability.
Alongside interaction design, I was responsible for shaping the visual language and component system to ensure consistency, clarity, and scalability.
Alongside interaction design, I was responsible for shaping the visual language and component system to ensure consistency, clarity, and scalability.
My Role & Scope
My Role & Scope
Lead Product Designer (AI & Interaction)
Lead Product Designer (AI & Interaction)
Lead Product Designer
3 months
3 months
3 months
Circle Global
Circle Global
Circle Global
AI interaction design, experience flows, visual design
AI interaction design, experience flows, visual design
AI interaction design, experience flows, visual design
Contact
Contact
Contact
Let's Get in Touch
Interested in collaborating or learning more? Feel free to reach out.