Apply for Machine Learning with Devops Developer Job

6 to 8 Years Relevant Experience

About the Role

We’re looking for an AI Security Engineer with hands-on expertise in AI/ML, cloud deployments, and security testing of Generative AI and LLM-powered solutions. This role is highly technical, research-driven, and will directly shape how we evaluate, validate, and secure emerging AI-driven cybersecurity tools.

Key Responsibilities

• Identify, analyze, and benchmark Generative AI–augmented and LLM-based security solutions in the market.
• Conduct proof-of-concept (PoC) assessments of cybersecurity capabilities to validate real-world effectiveness.
• Define security control baselines and evaluation criteria for emerging risk-focused solutions.
• Evaluate vendor claims, solution architectures, and scalability.
• Perform security testing of GenAI-powered cybersecurity tools.
• Publish detailed reports on security, compliance, and product efficacy.
• Build and integrate AI robustness, vulnerability, and stress testing capabilities within MLOps ecosystems.
• Assess and adapt open-source AI security libraries for enterprise-grade stress testing and audits.
• Implement secure model development lifecycle practices, including automated white-box and black-box assessments.
• Collaborate with application teams to ensure strong developer and customer experiences.
• Uphold Blue Box values in all interactions with internal and external teams.

Essential Skills

Must Have:

• Strong background in statistics, machine learning (DNN, NLP), big data, and data science toolkits.
• Proven experience designing and operationalizing high-performance AI/ML pipelines and production code.
• Experience deploying AI/ML models in public cloud environments.
• Familiarity with open-source ML tools, frameworks, and libraries.
• Proficiency in data science programming languages and toolkits.
• Experience with MLOps, DevOps, DataOps, and API integrations.
• Hands-on experience with AI workload management.
• Strong cloud architecture, design, and operational knowledge.

Good to Have:

• Knowledge of adversarial robustness techniques and AI risk management frameworks (e.g., Trustworthy AI).
• Familiarity with application security controls (Web, API, Mobile, AI).
• Understanding of security frameworks (NIST 800-53, CSF, OWASP ASVS).
• Knowledge of Secure SDLC, DevSecOps, and application security design.
• Experience with full-stack application architectures (SPAs, REST APIs, SOAP APIs, mobile).
• Background in Java, JavaScript, and mobile application development.
• Database expertise (Oracle, SQL, DB2, NoSQL).
• Cloud security design and operations knowledge.
• Exposure to IAM controls (OAuth 2.0, OIDC, JWT).
• Strong familiarity with cryptography (data at rest, in motion).
• Certifications: CISSP, CISM, CSSLP, CISA, CRISC.
• Peer-reviewed publications, conference presentations, or open-source contributions.