Job Description

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Key responsibilities:

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We are seeking a Vision AI Security Engineer to ensure the security, resilience, and trustworthiness of the VisionX platform, including computer vision solutions, AI/ML models, video analytics pipelines, and GenAI-powered capabilities.

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The ideal candidate will combine expertise in cybersecurity, AI security, and secure software engineering to identify, assess, and mitigate vulnerabilities, adversarial threats, model risks, and misuse scenarios across the end-to-end AI ecosystem.

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Location: Chennai, Noida, Bangalore, Hyderabad & Pune

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Skills

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- We are looking for a AI Security Engineer with minimum 8 years of experience.
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- Robust knowledge of application security, secure SDLC, threat modeling, vulnerability management, and security-by-design principles.
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- Hands-on experience with application security assessment tools such as OWASP ZAP, Burp Suite, SonarQube, SAST, DAST, SCA, and other enterprise security platforms.
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- Deep understanding of OWASP Top 10, API Security Top 10, authentication and authorization frameworks (OAuth2, JWT, SSO, RBAC), and access control mechanisms.
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- Proven experience securing web applications, APIs, cloud-native solutions, microservices, and enterprise integrations using modern security frameworks and best practices.
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- Proficiency in Python scripting and security automation to enable scalable security validation, monitoring, and DevSecOps implementations.
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- Strong understanding of AI/ML architectures, model lifecycles, data pipelines, and security considerations across AI-powered systems.
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- Experience securing GenAI and LLM-based applications, including protection against prompt injection, jailbreak attacks, unsafe outputs, model abuse, and data leakage risks.
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- Knowledge of RAG security principles, including grounding integrity, retrieval controls, source trust validation, vector database security, and prevention of unauthorized data exposure.
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- Understanding of AI-specific threat models, including adversarial attacks, data poisoning, model evasion, model theft, and privacy-related risks.
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- Experience assessing the security of computer vision and video analytics solutions, including image/video ingestion pipelines, inference services, edge AI deployments, and connected devices.
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- Familiarity with cloud security concepts across Azure, AWS, or GCP, including IAM, network security, secrets management, container security, and workload protection.
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- Strong knowledge of security monitoring, incident response, risk assessment, compliance, and governance frameworks relevant to AI and enterprise applications.
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📌 AI Security Engineer (Bengaluru)
🏢 HCLTech
📍 Bengaluru