AI Security Engineer
29 Oct 2025
Hyderabad, Telangana, India
Verified by Turrior
Content + Source + Freshness • 11 Dec 2025 • 95% confidence
75 / 100
Offer value
The role presents a balanced opportunity in securing AI systems, though lacks specific compensation data and may involve less visibility compared to top-tier firms.
- Role focused on securing AI models
- Cross-functional collaboration opportunities
- Lacks specific compensation details
- Entry-level experience may limit advancement
Pros
- Focus on a niche area within cybersecurity
- Opportunity to develop security protocols in AI
- Collaborative work across multiple functions
Cons
- Lack of defined salary and benefits structure
- Might be less prestigious than leading firms
- Entry-level experience may be limited
Who it's for
Early to Mid • On-site
Good fit
- Mid-career cybersecurity professionals
- Engineers looking to pivot into security
- Individuals interested in AI vulnerabilities
Not recommended for
- Newcomers seeking immediate promotions
- Candidates needing fully remote roles
- Those without a foundational cybersecurity background
Motivation fit
Desire to integrate AI with strong security paradigmsInterest in collaborative roles across disciplinesAspiration to influence organizational security strategies
Key skills
AI threat assessment capabilitiesExperience with security tools and protocolsFamiliarity with development frameworksCollaboration with cross-disciplinary teams
Score: 75/100 AI verified analysis
About the job
AI Security Engineer
Tracking Code
A25-148
Job Location
Unit No 902, 9th Floor, Building No 9, Raheja Mindspace, Survey No 64, TSIIC Software Units Layout H, Hyderabad, Telangana
Job Level
Mid Career
Category
Information Technology / Information Systems
Position Type
Full-Time/Regular
We are seeking a skilled and security-minded AI Security Engineer to join our team. In this role, you will be responsible for identifying and mitigating security risks in artificial intelligence systems, ensuring the confidentiality, integrity, and availability of AI models and data. You will work cross-functionally with data scientists, engineers, and cybersecurity teams to design, build, and maintain secure AI systems across their entire lifecycle.
Key Responsibilities
- AI Threat and Risk Assessment: Identify and assess AI-specific threats, including adversarial attacks, data poisoning, model inversion, and data leakage.
- Secure AI Pipeline Development: Implement security best practices throughout the AI/ML development lifecycle—from data ingestion and training to deployment and monitoring.
- Tooling & Automation: Develop and deploy tools for automated threat detection, model monitoring, and vulnerability scanning in AI workflows.
- Cross-functional Collaboration: Partner with software engineers, data scientists, DevOps, legal, and compliance teams to ensure secure and responsible AI development.
- Monitoring & Incident Response: Establish real-time monitoring, logging, and incident response procedures for AI systems in production.
- Compliance & Governance Alignment: Ensure alignment with relevant cybersecurity standards and AI-related regulations (e.g., ISO/IEC 27001, NIST, GDPR).
Required Skills
- Proficiency in Python; experience with AI/ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
- Solid understanding of cybersecurity fundamentals and secure software development practices.
- Experience with cloud platforms (AWS, Azure, or GCP) and securing cloud-native applications.
- Familiarity with security tools (e.g., static/dynamic analyzers, monitoring tools, threat modeling platforms).
- Experience building or securing large-scale ML infrastructure.
- Knowledge of privacy-preserving ML techniques (e.g., differential privacy, federated learning).
- Familiarity with AI governance, fairness, or explainability frameworks.
Required Experience
- 2–4 years of professional experience in cybersecurity, software engineering, or AI/ML system development
- AI certificate or Diploma can offset 1 year of work experience
- 1+ years working directly on securing AI/ML systems or data pipelines
