Security and AI Governance Lead

Infiniti Research; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Infiniti Research Bengaluru seeks an experienced governance professional to lead AI/ML governance, risk, and compliance initiatives within a highly regulated environment. You will define and enforce access controls, design audit trails, and supervise evaluation harnesses for AI outputs before deployment.

The role partners with legal and compliance, engineers, and solution architects to embed governance into system designs, monitor guardrails against misuse, and ensure transparent reporting to

Qualifications

• Demonstrated experience building or governing AI/ML systems in a regulated or high-compliance environment.
• Strong understanding of access control models (role-based, attribute-based) and entitlement enforcement patterns.
• Familiarity with AI safety and evaluation frameworks, including bias, groundedness, and adversarial-robustness testing.
• Experience with audit logging, data lineage, and reproducibility requirements.
• Working knowledge of data privacy regulations and privacy-by-design principles.
• Strong stakeholder communication skills — able to translate technical risk into business-relevant terms for leadership and auditors.
• Experience in pharmaceutical, healthcare, or other highly regulated industries.

Responsibilities

• Entitlements & Access Control: Define and enforce entitlement and access-control policies across all platform capabilities, ensuring data and model access are never granted beyond what a user's role permits.
• Audit Trail Design: Own the audit trail design so that every routing decision, model call, and human action is logged, reviewable, and reproducible.
• Evaluation Harness: Design and maintain the evaluation harness used to test AI outputs for accuracy, bias, safety, and policy compliance before and after release.
• Responsible-AI Reviews: Lead responsible-AI reviews for new capabilities, agents, or model changes prior to production rollout.
• AI Guardrails: Establish and monitor guardrails against prompt injection, data exfiltration, unsafe tool use, and other AI-specific risks.
• Data Classification & Privacy: Define data classification, redaction, and privacy-by-design requirements (e.g., PII/PHI handling) in partnership with legal and compliance stakeholders.
• Model Change Management: Own model versioning, rollback, and change-management policy so that any production issue can be traced and reversed.
• Audit & Compliance Liaison: Serve as the primary point of contact for internal and external audits, security reviews, and compliance questions related to the platform.
• Governance by Design: Partner with solution architects and engineering leads to ensure governance requirements are reflected in system design, not retrofitted after build.

Skills

AI governance

Regulated env

Data privacy

Audit logging

Job description

EXPERIENCE REQUIRED

810 years of experience in security, risk, or governance roles, including at least 3 years focused specifically on AI/ML governance, responsible AI, or model risk management.

KEY RESPONSIBILITIES

• Entitlements & Access Control: Define and enforce entitlement and access-control policies across all platform capabilities, ensuring data and model access are never granted beyond what a user's role permits.


• Audit Trail Design: Own the audit trail design so that every routing decision, model call, and human action is logged, reviewable, and reproducible.


• Evaluation Harness: Design and maintain the evaluation harness used to test AI outputs for accuracy, bias, safety, and policy compliance before and after release.


• Responsible-AI Reviews: Lead responsible-AI reviews for new capabilities, agents, or model changes prior to production rollout.


• AI Guardrails: Establish and monitor guardrails against prompt injection, data exfiltration, unsafe tool use, and other AI-specific risks.


• Data Classification & Privacy: Define data classification, redaction, and privacy-by-design requirements (e.g., PII/PHI handling) in partnership with legal and compliance stakeholders.


• Model Change Management: Own model versioning, rollback, and change-management policy so that any production issue can be traced and reversed.


• Audit & Compliance Liaison: Serve as the primary point of contact for internal and external audits, security reviews, and compliance questions related to the platform.


• Governance by Design: Partner with solution architects and engineering leads to ensure governance requirements are reflected in system design, not retrofitted after build.

QUALIFICATIONS

• Demonstrated experience building or governing AI/ML systems in a regulated or high-compliance environment.


• Strong understanding of access control models (role-based, attribute-based) and entitlement enforcement patterns.


• Familiarity with AI safety and evaluation frameworks, including bias, groundedness, and adversarial-robustness testing.


• Experience with audit logging, data lineage, and reproducibility requirements.


• Working knowledge of data privacy regulations and privacy-by-design principles.


• Strong stakeholder communication skills — able to translate technical risk into business-relevant terms for leadership and auditors.


• Experience in pharmaceutical, healthcare, or other highly regulated industries.