AI Governance

Systems Limited; India; On-site; INR 3,500,000 - 7,000,000; Full time

Job summary

Systems Limited is seeking a senior AI governance professional to design and implement governance for client engagements, conduct model risk assessments, and map engagement requirements to regulations such as EU AI Act and NIST RMF.

You will lead cross-functional governance reviews, train delivery teams on responsible-AI practices, and slow launches when risk warrants it, balancing commercial pressures with compliance.

Qualifications

• 6–12+ years in AI governance, model risk, compliance, or responsible-AI roles.
• Working knowledge of AI regulation (EU AI Act, NIST AI RMF, sector-specific frameworks) and how to operationalize it.
• Technical enough to critically assess a model card or evaluation report, not just check a box.
• Familiarity with bias/fairness testing methodologies and explainability tooling.
• Familiar with platform-native AI safety/governance tooling - Azure AI Content Safety, AWS Bedrock Guardrails, and Google Vertex AI safety filters; open-source evaluation tooling (Giskard, DeepEval) a good-to-have.
• Strong written policy/framework authorship - produces documents legal and technical teams both trust.
• Comfortable being the voice that slows down a launch when risk warrants it, under commercial pressure.
• Facilitates cross-functional governance reviews across legal, technical, and business stakeholders.

Responsibilities

• Design and implement AI governance frameworks and policy for client engagements
• Conduct model risk assessments and responsible-AI reviews before production go-live
• Own AI regulatory implementation - mapping engagement requirements to relevant regulation (EU AI Act, sector rules)
• Design and run AI red-teaming exercises for high-risk systems
• Own AI testing & evaluation standards from a governance/ethics lens (bias, fairness, explainability, AI ethics)
• Advise practice leads and Architects on governance risk during solution design, not just at the end
• Facilitate cross-functional governance reviews across legal, technical, and business stakeholders
• Be the voice that slows down a launch when risk warrants it, under commercial pressure
• Train delivery teams on responsible-AI practices

Skills

AI governance

Model risk

Compliance

Responsible-AI

Regulation knowledge

Bias testing

Explainability tooling

Platform safety tooling

Policy authorship

Stakeholder management

Tools

Giskard

DeepEval

Azure Content Safety

AWS Bedrock Guardrails

Vertex AI Safety

Job description

Makes AI systems trustworthy and compliant - governance frameworks, model risk assessment, and regulatory implementation that keep delivery out of legal and reputational trouble.

KEY RESPONSIBILITIES

• Design and implement AI governance frameworks and policy for client engagements
• Conduct model risk assessments and responsible-AI reviews before production go-live
• Own AI regulatory implementation - mapping engagement requirements to relevant regulation (EU AI Act, sector rules)
• Design and run AI red-teaming exercises for high-risk systems
• Own AI testing & evaluation standards from a governance/ethics lens (bias, fairness, explainability, AI ethics)
• Advise practice leads and Architects on governance risk during solution design, not just at the end
• Facilitate cross-functional governance reviews across legal, technical, and business stakeholders
• Be the voice that slows down a launch when risk warrants it, under commercial pressure
• Train delivery teams on responsible-AI practices

REQUIREMENTS & SKILLS

• 6-12+ yrs in AI governance, model risk, compliance, or responsible-AI roles
• Working knowledge of AI regulation (EU AI Act, NIST AI RMF, sector-specific frameworks) and how to operationalize it
• Technical enough to critically assess a model card or evaluation report, not just check a box
• Familiarity with bias/fairness testing methodologies and explainability tooling
• Familiar with platform-native AI safety/governance tooling - Microsoft Azure AI Content Safety, AWS Bedrock Guardrails, and Google Vertex AI safety filters; open-source evaluation tooling (Giskard, DeepEval) a good-to-have
• Strong written policy/framework authorship - produces documents legal and technical teams both trust
• Comfortable being the voice that slows down a launch when risk warrants it, under commercial pressure
• Facilitates cross-functional governance reviews across legal, technical, and business stakeholders
• Diplomatic but firm - holds the line on risk without becoming an obstructionist