AL/ML Security - Information Security

• Identify, analyze, and benchmark Generative AI augmented, LLM agentic security solutions in the market.
• Conduct proof-of-concept (PoC) assessments of selected cybersecurity capabilities to validate effectiveness in real-world environments.
• Define security control baselines and evaluation criteria for emerging risk security solutions.
• Evaluate vendor claims, solution architecture, and technical scalability.
• Security testing of GenAI-powered cybersecurity tools.
• Publish detailed reports on the security, compliance, and efficacy of evaluated products.
• Deliver and integrate AI robustness, vulnerability, and stress testing capabilities with MLOps ecosystems.
• Evaluate and assess open-source AI security libraries to build into enterprise AI stress testing and audit capabilities.
• Implement secure model development life cycle practices with automated white box and black box assessments for AI/ML models.
• Consistently enable strong developer and customer experience when liaising with application teams. Uphold Blue Box values when liaising with application teams.
• Minimum Qualifications:
• Bachelor’s Degree in Data Science, Statistics, Computer Science or Software Engineering 2+ years’ experience with Machine Learning Application Development 3+ years of software engineering experience.

Preferred Qualifications:

• Master’s Degree - Data Science, Statistics, Computer Science, or Software Engineering Machine Learning Operation Professional Certifications Demonstrated peer reviewed journal publications, conference presentations, open-source contributions, or similar activities.
• Strong knowledge of Adversarial Robustness techniques and tools for machine learning.
• Strong knowledge of AI Risk Management frameworks and Trustworthy AI practices.
• Hands-on experience with applying statistics, machine learning algorithms (DNN, NLP), big data, and data science toolkits. Hands-on experience designing, implementing, and operationalizing high performant AI/ML pipelines and writing production code.
• Hands-on experience with deploying and operationalizing AI/ML models to public cloud environments.
• Hands-on experience evaluating open-source ML tools, frameworks, and libraries.
• Hands-on experience with commonly used data science programming languages, packages, and tools.
• Hands-on experience with MLOps, DevOps, DataOps and API integrations.
• Hands-on experience with AI workload management.
• Hands-on experience with Cloud architecture, design, implementation, and operations.
• Knowledge of application security controls (Web, API, Mobile, AI).Knowledge of security domains, common information security management and application frameworks: NIST 800-53, CSF, OWASP ASVS.
• Knowledge of Secure SDLC , Application Security design and DevSecOps Full stack knowledge of application architectures including: Single Page Applications, REST APIs, SOAP APIs, Mobile Applications.
• Experience with Java, Javascript and mobile application development.
• Knowledge or familiarity with database architectures including Oracle, SQL, DB2 and NoSQL Databases.
• Experience with Cloud security, architecture, design, implementation, and operations.
• Exposure to IAM Controls (OAuth 2.0, OIDC, JWT)Strong familiarity with Cryptography Controls (Data at rest, in motion).Certification - CISSP, CISM, CSSLP, CISA, CRISC