We are looking for a Principal Applied AI Scientist to lead the design and deployment of cutting-edge Generative AI and LLM-powered systems for real-world, high-impact applications. This is a senior, hands-on leadership role for someone who can operate across the full stack of modern AI - from research and modeling to production systems and productization - while leading teams and defining technical direction. You will work at the intersection of LLMs, agentic systems, retrieval architectures, and large-scale AI platforms, building systems that move beyond prototypes into robust, production-grade intelligence systems. What You'll Do - Lead the end-to-end design and development of large-scale AI/ML and Generative AI systems - Architect and deploy LLM-powered applications, including RAG pipelines and multi-agent systems - Drive the technical vision and roadmap for applied AI across the company - Build and lead a high-performing team of scientists and engineers - Design scalable retrieval and embedding systems powering intelligent applications - Develop agentic AI systems with tool use, memory, and reasoning capabilities - Own model lifecycle: data curation  training/fine-tuning  evaluation  deployment  monitoring - Partner with product, engineering, and executive leadership to translate business problems into AI solutions Required Qualifications - 7+ years of experience in Applied AI / Machine Learning / Generative AI - Proven experience building and deploying production-grade AI systems at scale - Demonstrated leadership managing large cross-functional teams - Strong experience engaging with executives and product stakeholders - Deep expertise in LLMs, RAG, and agentic AI systems at scale - Strong system design skills across data, models, and infrastructure - Ability to move from research ideas  production systems  business impact - Strong ownership mindset with the ability to operate in fast-moving startup environments - Experience with multi-agent orchestration frameworks and tool ecosystems Preferred Qualifications - Experience applying AI in cybersecurity, enterprise SaaS, or data-intensive domains - Background in search or large-scale retrieval systems Core Technical Expertise - Large Language Models & GenAI - RAG, Retrieval & Vector Systems - Fine-Tuning & Model Adaptation - Agentic AI Systems - Prompt Engineering & Optimization - Evaluation & Quality - Inference & Serving - Data Engineering & Synthetic Data - Multimodal AI - LLMOps & Observability - Platforms & Infrastructure