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