Reflections Info Systems - Senior AI Security & Governance Engineer - Cyber Security

Vista Info Systems; Kolkata District; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

Vista Info Systems is seeking a Senior AI Security & Governance Engineer to embed responsible AI controls directly into runtime systems. You will assess risk and implement controls beyond policy docs.

The role demands deep technical depth, hands-on design of prompt filtering, output validation, and misuse protection to govern AI agents across deployments. Strong experience in security or governance systems is essential.

Qualifications

• 5–9 years of engineering experience.
• Strong Python and scripting skills.
• Experience with security or governance-related systems.
• Experience with policy-as-code or rule engines.
• Deep 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

Scripting

Security systems

Policy-as-code

AI risks

Compliance mindset

AI governance

Job description

About The Role

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)