Applied AI Engineer (Member of Technical Staff)

Proven track record of shipping LLM-powered products or features, and/or personal projects using LLMs. Familiarity with prompt engineering, Retrieval-Augmented Generation, and other techniques to improve the performance of LLMs on domain-specific problems. Understanding of foundation model APIs, context engineering, model evaluation, fine-tuning techniques, and safety considerations. Prior experience in building machine learning/NLP systems. Passionate about LLM research and keeping up to date with developments in machine learning and Generative AI. Experience and/or interest in designing and scaling engineering systems, with a focus on machine learning and LLMs, and ability to write production code. Excellent communication skills.

Lead the architecture, design, and development of our Agentic AI platform. Use in-context learning, prompt engineering, and retrieval-based context augmentation methods to improve LLM performance on security-specific tasks. Shape the architecture of our machine learning solutions, making strategic decisions on model configurability, portability, and cost. Design evaluation methodologies, guidelines, metrics, and infrastructure to measure the performance of our machine learning systems. Stay at the forefront of NLP/ LLM research and explore the potential of new foundation models on domain-specific tasks. Establish comprehensive guardrails for safe and responsible use of LLMs.