Data Security in AI Engineer

AI Security, Privacy & Compliance

Location: Netaji Subhash Place (NSP), Delhi

Work Mode: On-site / Hybrid

Employment Type: Full-Time

Experience: 3–7+ Years

Salary: As per experience and technical expertise

Job Overview

We are looking for an experienced Data Security in AI Engineer who can design, implement, and maintain secure AI systems, data pipelines, and enterprise AI applications. The ideal candidate should understand both cybersecurity principles and modern AI architectures, ensuring that sensitive business and customer information remains protected throughout the AI lifecycle.

This role requires hands-on expertise in securing:

- LLM-based applications
- RAG systems
- AI agents
- Data pipelines
- Cloud infrastructure
- Document processing systems
- Enterprise business automation platforms

The candidate should be capable of identifying security risks, analyzing root causes, implementing controls, and ensuring compliance with security and privacy standards.

Key Responsibilities

- Design and implement security controls for AI-powered applications.
- Secure LLM, RAG, and AI agent architectures.
- Identify vulnerabilities in AI workflows and data pipelines.
- Establish data governance and privacy frameworks.
- Design secure authentication and authorization systems.
- Implement encryption for data at rest and in transit.
- Conduct threat modelling for AI systems and APIs.
- Secure vector databases and knowledge repositories.
- Implement role-based access controls (RBAC).
- Monitor and detect anomalous AI system behaviour.
- Secure document processing, OCR, and extraction systems.
- Prevent prompt injection, jailbreak, and data leakage attacks.
- Design data masking, anonymisation, and redaction solutions.
- Create audit logs and compliance reporting mechanisms.
- Conduct vulnerability assessments and penetration testing.
- Secure cloud environments and AI deployments.
- Implement secrets management and key rotation processes.
- Establish incident response procedures for AI systems.




- Review existing applications and improve security posture.
- Ensure compliance with privacy and regulatory requirements.

Required Technical Skills Security & Privacy

- Application Security
- Data Security
- Network Security Fundamentals
- Identity & Access Management (IAM)
- RBAC & ABAC Models
- OAuth 2.0
- OpenID Connect
- SSO Integration
- Security Auditing
- Risk Assessment
- Threat Modelling

AI Security

- LLM Security
- Prompt Injection Defense
- AI Red Teaming
- RAG Security
- Model Risk Assessment
- AI Agent Security
- Secure Tool Calling
- Secure Prompt Engineering
- Data Leakage Prevention
- Model Monitoring
- AI Governance

Backend & Development

- Python
- Fast API
- Node.js
- REST APIs
- API Security
- Web Security
- Secure Coding Practices

Database Security

- PostgreSQL
- MongoDB
- Redis
- Data Encryption
- Database Access Controls
- Data Retention Policies
- Backup & Recovery

Cloud & Infrastructure

- AWS / GCP / Azure
- Docker
- Kubernetes
- Linux
- CI/CD Security
- Infrastructure as Code
- Logging & Monitoring

Security Tools

- SIEM Platforms
- WAF Solutions
- Vault / Secrets Manager
- Security Scanners
- Vulnerability Assessment Tools
- Endpoint Security Solutions

Preferred Experience

- AI Security Audits
- Enterprise Data Governance
- ISO 27001 Implementation
- SOC 2 Compliance
- GDPR Compliance
- DPDP Act (India) Compliance
- Cloud Security Architecture
- AI Risk Management Frameworks
- Secure Multi-Tenant Platforms
- Financial or Legal Technology Security
- Zero Trust Architecture
- Security Operations (SOC)

What We Are Looking For The most significant requirement is security-focused problem solving and ownership. We need someone who can say:





“I understand the security risk, this is the root cause, these are the potential attack vectors, this is the mitigation plan, and I can implement the controls within this timeframe.”

The candidate should

- Work independently with minimal supervision.
- Think like both an engineer and a security analyst.
- Identify risks before they become incidents.
- Design secure-by-default systems.
- Deliver practical security solutions without slowing down business operations.
- Communicate security findings clearly to technical and non-technical stakeholders.
- Stay updated with evolving AI and cybersecurity threats.

Experience 3–7+ years of relevant experience in cybersecurity, application security, cloud security, AI security, or data protection.

Experience securing production AI applications, cloud environments, or enterprise platforms is highly preferred.

Education

- B.Tech / B.E. / MCA / M.Tech / Cyber Security or equivalent qualification preferred.
- Relevant certifications will be considered an advantage.

Preferred Certifications

- CISSP
- CEH
- CompTIA Security+
- CCSP
- AWS Security Specialty
- Azure Security Engineer Associate
- ISO 27001 Lead Implementer
- AI Security Certifications

Ideal Candidate Profile The ideal candidate has experience securing:

- AI Agents
- RAG Systems
- LLM Applications
- CRM Platforms
- Document AI Systems
- Customer Data Platforms
- Cloud Infrastructure
- Enterprise Workflow Automation Solutions

and understands the intersection of AI, cybersecurity, data privacy, and business risk. This version is designed specifically for organisations building AI products, LegalTech platforms, document-processing systems, CRM solutions, and AI automation tools. It aligns well with the responsibilities and technology stack in your original AI Engineer JD.

Pay: ₹30,000.00 - ₹50,000.00 per month

Application Question(s)

- Where you reside in delhi ?
- What is your Last CTC ?
- Total years of experience you have ?

Work Location: In person

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