Infosys
Website:
infosys.com
Company:
https://www.linkedin.com/company/infosys
Seniority: Mid-Senior level
Industries: IT Services and IT Consulting
Job details:
Responsibilities
- AI Security Evaluations: Conduct structured adversarial testing, vulnerability analysis, and security assessments on AI models, datasets, and pipelines to identify technical weaknesses.
- Design AI Security Testing Methodologies: Develop evaluation strategies, attack simulations, and test cases that examine model behavior under adversarial and stress conditions.
- Analyze Model Vulnerabilities: Review model outputs, logs, and error patterns to detect indicators of poisoning, evasion, extraction attempts, or unsafe behavior requiring mitigation.
- Support Development of AI Defense Mechanisms: Contribute technical insights for designing and implementing guardrail components, safety filters, validation controls, and secure model behavior constraints.
- Conduct Research on Emerging AI Threats: Study new attack surfaces such as prompt injection, model inversion, indirect influence attacks, and supply chain vulnerabilities relevant to modern AI systems.
- Build Security Testing Scripts and Pipelines: Create and maintain scripts, automation tasks, and evaluation pipelines that streamline security testing, red team simulations, and model behavior monitoring.
- Document AI Security Findings: Prepare technical reports, vulnerability summaries, experiment results, and evidence artifacts that support security reviews and R&D decision-making.
- Collaborate with Cross Functional Teams: Work with engineering, Responsible AI, cybersecurity, and data science teams to jointly investigate issues and integrate necessary security improvements.
- Secure Model Deployment Activities: Assist in validating the security posture of models before deployment by verifying guardrail integration, access controls, and vulnerability remediation.
- Monitor Emerging AI Security Tools and Techniques: Continuously evaluate new defensive methods, adversarial testing libraries, and AI security research to enhance testing capabilities and inform tooling upgrades.
Technical and Professional Requirements:
- Strong proficiency in Python with experience building security evaluation scripts and adversarial testing utilities.
- Knowledge of adversarial ML techniques including evasion, poisoning, extraction, inversion, and prompt manipulation methods.
- Familiarity with adversarial testing frameworks and libraries (e.g., TextAttack, IBM ART, PyRIT, MITRE ATLAS tools).
- Understanding of ML and DL model behavior, architecture vulnerabilities, and LLM‑specific attack vectors.
- Experience with red‑team style testing for LLMs, RAG systems, and multimodal AI systems.
- Knowledge of MLOps/LLMOps workflows and integrating security tests into CI/CD evaluation pipelines.
Preferred Skills
Technology->AI-Responsible AI->Responsible AI->explainable ai
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