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Armis from ServiceNow is building an autonomous defense platform for the Agentic Enterprise, combining cybersecurity, identity security, and AI capabilities. The company protects attack surfaces and manages cyber risk exposure in real time using machine learning and generative AI as core engines.
You will join the Vulnerability Management, Detection, and Remediation (VMDR) team as a Staff AI Engineer, taking end-to-end ownership of complex AI and ML initiatives. Your responsibilities include:
• Drive complex AI and ML initiatives through the full product lifecycle, from early-stage prototyping and domain analysis to production-grade deployment and monitoring.
• Design and build production-ready AI models and system pipelines in Python using modern cloud and big data infrastructure (AWS, Spark).
• Integrate state-of-the-art Generative AI and LLM workflows into core VMDR features to enable automated detection, prioritization, and remediation insights.
• Partner closely with domain researchers, data engineers, and product leaders to translate complex cybersecurity problems into high-impact AI solutions.
• Act as a technical builder owning complex problem domains end-to-end, diving deep into cybersecurity nuances and architecting cutting-edge LLM and ML solutions.
This is a high-impact role where you will shape the future of AI-driven cybersecurity at scale within a Fortune 500 company.
REQUIREMENTS:
• Cybersecurity background: Domain experience in Vulnerability Management, Asset Intelligence, or Threat Detection is advantageous but not mandatory.
• LLM expertise: At least 2 years of hands-on experience with Large Language Models, including prompt engineering, fine-tuning, RAG, agentic workflows, and orchestration frameworks (LangChain, LlamaIndex, vLLM, or similar).
• Solid ML foundations: Deep algorithmic and theoretical knowledge in Machine Learning, supported by an M.Sc. or Ph.D. (or equivalent research experience).
• Production engineering skills: 5+ years of software development experience with strong, production-grade Python coding and experience deploying ML systems at scale.
• Self-driven and collaborative: Autodidact who takes full ownership of problem domains, stays ahead of emerging AI trends, and thrives in high-trust, collaborative environments.
