Governance & Trust Engineering

Frost & Sullivan

. Make research-to-software solutions trustworthy by turning research standards, data permissions and AI risks into practical controls, test evidence and accountable release decisions .

Posted 10/7/2026full-timeSingapore • SingaporeMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in research quality assurance, risk management, and data governance, with a strong focus on AI output evaluation and compliance. Proficient in SQL and Python for implementing controls and conducting audits in a privacy-focused environment.

Highest-signal resume keywords

Research Quality AssuranceRisk ManagementData GovernanceSQL/Python ProficiencyAI Output Evaluation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Research QualityData GovernanceRisk AssessmentSQLPythonAccess-Control TestingLogging ExperienceAuditControl ImplementationChange Records

Soft Skills

Clear Evidence-Based WritingStructured Risk JudgmentConstructive Challenge

Industry Keywords

AI RisksPrivacy-By-DesignSecurity TestingData ProvenanceAI Assurance Frameworks

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Make research-to-software solutions trustworthy by turning research standards, data permissions and AI risks into practical controls, test evidence and accountable release decisions
Maintain registers for datasets, models and decision workflows
Track ownership, source licences, consent or other applicable permissions, confidentiality, retention, approved uses and restrictions
Conduct legal/privacy review where needed
Create research-quality, evidence, uncertainty and human-review requirements
Design tests for unsupported claims, inaccurate citations, numerical errors, bias and unsuitable recommendations
Record exceptions and remediation
Specify role permissions, approval gates, audit events and tenant-isolation tests with engineers
Maintain risk assessments, model documentation, change records and release evidence
Coordinate red-team findings, incident escalation, rollback exercises and advisor acceptance
Report risks independently from delivery pressure

Requirements

What you’ll need

Strong record in research quality, consulting delivery assurance, audit, risk, data governance or a related field
Typically 4+ years of experience, with equivalent achievement considered
Clear evidence-based writing
Structured risk judgment
Constructive challenge
Basic AI learning
Practical ability to identify and explain AI output failures
Preferred exposure to responsible AI, privacy-by-design, security testing, data provenance or AI assurance frameworks
SQL/Python, access-control testing and logging experience are useful
Hands-on coding and control implementation are required for appointment to the Engineer variant

Benefits

Comp & perks

Access to privacy, security and advisory approvers
Human-reinforced AI insights and analytics environment
Professional exposure to Frost & Sullivan’s industry expertise, enterprise data and third-party insights