feat(privacy): add AI resume bias detection and candidate anonymization engine

[dipanshubatra]

Summary

Implement an AI-driven resume bias detection and candidate anonymization engine focused on blind hiring, skill-based candidate evaluation, text inclusivity analysis, and GDPR/CCPA privacy redaction.

Changes Proposed

• Detect and anonymize candidate personally identifiable information (PII).
• Redact names, emails, phone numbers, locations, and university prestige indicators.
• Enable blind candidate profile evaluation based on technical qualifications.
• Evaluate candidates using code quality and skills without identity-related information.
• Analyze gender-coded language for text inclusivity.
• Add GDPR/CCPA privacy redaction rules.
• Support enterprise blind hiring privacy and diversity evaluation workflows.

Technical Details

Resume Bias Anonymization

• Detect candidate PII within resumes.
• Anonymize names, emails, phone numbers, and locations.
• Handle university prestige information as part of candidate anonymization.
• Provide AI-driven bias detection and anonymization functionality.

Blind Hiring Evaluation

• Evaluate candidate profiles based on skills and technical qualifications.
• Focus assessment on code quality and technical capabilities.
• Remove identity-related signals from blind candidate evaluation.

Text Inclusivity

• Analyze resume text for gender-coded language.
• Provide text inclusivity analysis for candidate-facing content.

Enterprise Diversity Audit

• Provide enterprise-oriented diversity and blind hiring evaluation functionality.
• Support evaluation workflows focused on reducing identity-based hiring bias.

Privacy Redaction

• Implement GDPR/CCPA privacy redaction rules.
• Provide privacy-focused candidate data redaction for blind hiring workflows.

Dashboard

No dashboard was reported in the implementation report.

Testing

Dedicated test files were added for all implemented services and utilities. No specific executed test status or coverage percentage was reported.

Acceptance Criteria

• Candidate names can be anonymized.
• Candidate email addresses can be anonymized or redacted.
• Candidate phone numbers can be anonymized or redacted.
• Candidate locations can be anonymized or redacted.
• University prestige information can be handled during anonymization.
• Candidate profiles can be evaluated based on technical qualifications.
• Code quality can be used as a blind hiring evaluation signal.
• Gender-coded text can be analyzed for inclusivity.
• GDPR/CCPA privacy redaction rules are implemented.
• Dedicated tests are provided for the implemented services and utilities.

[github-actions]

👋 Thank you @dipanshubatra for opening this issue!

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[github-actions]

✅ This issue was resolved by PR #1162.

Thanks for reporting — the fix is now on main.