Senior Security Engineer AI/ML

Required Qualifications

• 5+ years of experience in security research, penetration testing, or exploit development, with a focus on application or cloud security.
• Strong working knowledge of machine learning and LLM architectures (e.g., transformers, embeddings, fine-tuning, RAG).
• Familiarity with GenAI-specific risks such as prompt injection, model evasion, hallucination-based exploits, data leakage, or model theft.
• Experience in scripting and automation using Python (preferred) or similar languages for testing and PoC development.
• Hands-on understanding of LLM deployment scenarios (e.g., OpenAI, HuggingFace , custom-hosted models) and threat surfaces involved.
• Ability to analyze logs, API interactions, inference responses, and prompt chains to identify anomalous or risky behavior.
• Strong analytical mindset, technical writing skills, and the ability to communicate complex vulnerabilities clearly.
• Familiarity with responsible disclosure practices, bug bounty programs, or security research ethics.

Preferred Qualifications

• Background in AI/ML security red teaming or adversarial ML.
• Knowledge of vector database risks, insecure RAG pipelines, model fingerprinting, and AI model supply chain attacks.
• Experience using or contributing to tools like LangChain , AutoGen , Guardrails.ai, LLM Guard, or Tracer.
• Publications or presentations in conferences like Black Hat, DEF CON, USENIX, NeurIPS , or OWASP.
• Familiarity with Secure SDLC, threat modeling frameworks (e.g., STRIDE, MITRE ATLAS), and AI-specific security checklists.

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