Senior AI/LLM Engineer

Censys is seeking a Senior Software Engineer for its SOC/TH team focused on AI and LLMs. The role builds AI-powered investigation workflows and features for the Censys Platform, including LLM and RAG pipelines, analytics and automation systems, and model evaluation and testing.

Responsibilities:

• Rapidly prototype and deploy AI-powered features to enhance search, improve recommendations, and automate workflows across the Censys Platform
• Apply machine learning to streamline workflows, personalize experiences, and surface critical insights
• Develop and fine-tune LLMs and RAG pipelines to reason over Internet-scale data, summarize findings, and deliver context-aware insights
• Build, scale and maintain AI-driven analytics and automation systems helping users make faster, data-backed decisions
• Collaborate with frontend, product, and data engineering teams to integrate AI-native experiences that feel seamless, intuitive, and secure
• Continuously evaluate and improve model performance through RAGAS, LangSmith, and automated regression testing frameworks

Requirements:

• 5+ years of software engineering experience, including 2+ years building and scaling AI-powered user-facing features
• Strong proficiency in Python for backend and API services development
• Familiarity with RAG evaluation frameworks (e.g., RAGAS, LangSmith) and designing regression testing for LLM pipelines
• Ability to rapidly prototype, validate and refine AI features in a fast-paced, experiment-driven environment
• Prior knowledge in prompt engineering improving LLM accuracy, reasoning and consistency
• Understanding secure and responsible AI practices, implementing guardrails and safety checks to prevent misuse or data exposure
• Hands-on experience with CI/CD pipelines, test automation, and deployment best practices for AI applications
• Strong cross-team collaboration to ensure AI capabilities elevate the overall user experience on the Platform
• Leveraging AI tools as a force multiplier to code smarter, iterate faster boosting productivity and improving product capabilities
• Advanced knowledge of AI/ML architectures, model evaluation, and applied deep learning
• Experience with retrieval-augmented generation (RAG), vector search, and LLM fine-tuning
• Understanding of embedding models and AI-driven analytics
• Proven ability to optimize AI models for low-latency, real-time interactions in browser or frontend environments
• Experience deploying secure AI systems in cybersecurity or other sensitive data domains