Support the deployment and evaluation of cybersecurity platforms and tools such as Mythos , vulnerability management, and security assessment solutions. Experiment with LLMs, RAG systems, prompt engineering, and agent-based workflows.

Build detection at scale. Design and ship security workflows that combine deterministic analysis (taint, reachability, static slicing) with LLM reasoning to find real vulnerabilities (SSRF, IDOR, injection, auth gaps, supply-chain risk, and beyond) across many languages and frameworks. Make LLMs viable for security-critical work. Engineer agentic pipelines and prompts that are precise, cost-aware, and trustworthy: atomic, well-scoped steps grounded in deterministic context, with attention to hallucination, confidence calibration, and which models see sensitive code.

Own end-to-end test strategy and execution for AI/ML models, GenAI, LLMs, and multi-agent systems, spanning functional, adversarial, safety, and security testing. Design evaluation frameworks to measure hallucination rate, bias, toxicity, and prompt-response consistency.