Job Description
Role Summary
You design, build, and run security controls for artificial intelligence systems across the full lifecycle. You secure model development, training data, pipelines, APIs, and AI-enabled applications. You work with product, engineering, data science, and compliance teams to reduce exposure from model misuse, data leakage, supply chain threats, and adversarial attacks. You deliver measurable improvements in AI governance, detection, and incident response.
Key Responsibilities
Secure the AI and ML lifecycle
- Define security requirements for model development, training, evaluation, deployment, and monitoring
- Threat model AI systems and AI features in products, including abuse cases and misuse scenarios
- Establish secure-by-design patterns for model endpoints, prompts, RAG pipelines, and agent workflows
- Validate controls for model access, rate limiting, tenant isolation, and secrets management
Required Qualifications
- Bachelor’s degree in Cybersecurity, Artificial Intelligence, Computer Science, or related highly technical field
- 5+ years in security engineering, application security, cloud security, or detection engineering
- Experience securing LLM-based applications, RAG systems, or agentic workflows
- Familiarity with adversarial ML concepts, such as prompt injection, model inversion, and model extraction
- Experience with one or more cloud platforms, AWS, Azure, or GCP
- Experience with Kubernetes and container security
- Hands-on experience with at least one programming , Python
- Strong understanding of AI, LLMs, API security, , secrets management, and cloud controls
- Experience building security controls into CI and CD pipelines
- Proven ability to lead cross-functional security work with engineering and product teams
- Effectively communicate complex technical concepts to both technical and non-technical stakeholders
- Effectively communicate to leadership and know when to escalate with proactive, clear, data-driven insight, highlighting risks, roadblocks, and solutions
- Proven leadership capabilities with the ability to influence and drive change
Qualifications
- Master’s degree in Cybersecurity, Artificial Intelligence, Computer Science, or related highly technical field
- AI/ML certifications (e.g., Microsoft Azure AI Engineer, AWS ML Specialty, GIAC Machine Learning Engineer, ISC2 Building AI Strategy)
- Experience with security telemetry and detections in SIEM or EDR platforms