Reflections Info Systems - Senior AI Security & Governance Engineer

Vista Info Systems; Kolkata District; On-site; INR 4,000,000 - 6,500,000; Full time

Job summary

Vista Info Systems in India seeks a Senior AI Security & Governance Engineer to embed responsible AI controls directly into runtime systems. This role requires deep technical expertise and strong risk judgment beyond policy documentation.

You will design and implement prompt filtering, output validation, and misuse protection, enforce AI governance through code and automation, build audit trails and control mechanisms, and advise on AI risk scenarios and failure modes.

Qualifications

• 5 to 9 years of engineering experience.
• Strong Python / scripting.
• Experience with security or governance-related systems.
• Experience with policy-as-code or rule engines.
• Strong understanding of AI risks (hallucinations, prompt injection, data leakage).
• Enterprise compliance mindset.

Responsibilities

• Design and implement prompt filtering.
• Design and implement output validation.
• Design and implement misuse protection.
• Enforce AI governance through code and automation.
• Build audit, traceability, and control mechanisms.
• Define safety patterns used across all AI agents.
• Advise on AI risk scenarios and failure modes.

Skills

Python

Security systems

Governance

Policy-as-code

AI risk knowledge

Enterprise compliance

Job description

We are looking for a Senior AI Security & Governance Engineer to embed responsible AI controls directly into runtime systems.

This role requires strong technical depth and risk judgment not policy documentation.

Required Skills & Experience

• 5 to 9 years of engineering experience.
• Strong Python / scripting.
• Experience with security or governance-related systems.
• Experience with policy-as-code or rule engines.
• Strong understanding of AI risks (hallucinations, prompt injection, data leakage).
• Enterprise compliance mindset.

Key Responsibilities

• Design and implement prompt filtering.
• Design and implement output validation.
• Design and implement misuse protection.
• Enforce AI governance through code and automation.
• Build audit, traceability, and control mechanisms.
• Define safety patterns used across all AI agents.
• Advise on AI risk scenarios and failure modes.

(ref:hirist.tech)