AI Chat Assistant & Knowledge Engineering Intern

Remote Full-time
100% | 6 months asap| remote in Switzerland/Germany or from our Zurich officeAbout Exeon:Exeon is a leading cybersecurity scale-up with Swiss roots, pioneering AI-driven security analytics to protect IT, OT, and IoT networks. Born from ETH Zurich innovation, our flagship solution, Exeon.NDR, empowers enterprises to monitor, detect, and respond to threats with unmatched speed and accuracy. We combine Swiss excellence with a flexible, remote-first, and collaborative culture, supporting passionate, ambitious professionals devoted to solving cybersecurity challenges and driving continuous innovation.As an AI Chat Assistant & Knowledge Engineering Intern at Exeon, you will help design, build, evaluate, and continuously improve an internal AI assistant that supports engineers, security analysts, and business stakeholders. Equally important, you’ll take a leading role in organizing and transforming our internal documentation (technical specs, API docs, runbooks, playbooks, product guides, research notes, etc.) into structured, machine consumable knowledge assets that power high quality responses. You will work closely with an Exeon mentor in the field of AI and collaborate with subject matter experts across Security Engineering, Product, Customer Success, and Technical Writing. In particular, you will:AI Chat Assistant Development (≈50%): Extend and refine Exeon’s internal LLM powered assistant (initially for internal use; potential future externalization). Build and iterate on a retrieval augmented generation (RAG) stack: document ingestion, chunking, embeddings, vector search, ranking, answer synthesis. Design and run offline & human‑in‑the‑loop evaluation experiments (precision/recall of retrieval, response helpfulness, hallucination rate, latency & cost metrics). Knowledgebase & Documentation Engineering (≈50%): Add missing technical content to the existing guides relevant for improving the LLMs accuracy and ability to reason about the content. Rewrite or refactor technical material for clarity, consistency, and LLM‑friendly structure (FAQ patterns, Q&A primitives, procedure steps). Contribution guidelines: Draft lightweight authoring standards so ongoing documentation remains assistant‑ready and user-friendly. What you can expect from us:An innovative scale-up environment with leading-edge security software and a fast-growing European presence. Autonomy, flexibility (remote options), and trust, empowering you to shape your role and contributions. Hands-on collaboration with Security Experts, Data Scientists, and Business Professionals from across Europe. Clear growth opportunities and support for personal and professional development. Open, diverse, and inclusive culture committed to independent thinking and work-life balance. RequirementsWhat makes a good person-job-fit:We are looking for a proactive, self-motivated and enthusiastic AI enthusiast who is comfortable in a high-paced start-up environment and who shares our values. In addition, we are looking for certain requirements and skills to establish a good person-job-fit: An enthusiastic student who enjoys research, has strong communication skills, and the ability to work independently and proactively. Currently pursuing or holding a Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or a related field. Ability to reorganize messy information into structured, navigable, well‑labelled content. Strong written communication in English; clear, concise, audience‑aware writing. Proficiency in Python and experience with at least one AI/LLM application framework such as LangChain, Haystack, Semantic Kernel, etc. or strong willingness and demonstrated capacity to learn quickly. Strong interest in cybersecurity.Basic understanding of embeddings, vector databases, or information retrieval concepts. Strong analytical and problem-solving skills with an interest in technical and organizational innovation. Comfortable using Git/GitHub/GitLab for collaborative development. Originally posted on Himalayas

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