Vp r&d

We are a fast-growing, AI-driven company dedicated to solving some of the world's most vital geopolitical challenges through technology and advanced data analysis. We leverage cutting-edge Large Language Models (LLMs) and big data engineering to transform elite scientific research into a powerful, scalable product. Our mission is to empower scientists and strategists and play a pivotal role in global decision-making and innovation by developing high-impact, production-grade systems in a hands-on, collaborative, and technically excellent environment.We are at the pre-seed stage and offering the opportunity to join the company early and shape the product.Head of Research & Development (R&D)The Head of R&D would lead the company's efforts in translating cutting-edge scientific research, particularly in LLMs and big data, into practical, powerful technological solutions. This role is focused on the innovation and architecture of the core AI models and data pipelines that drive the company's intelligence tools. In addition the R&D head will be tasked with building and managing the engineering team.Core Responsibilities:Team Management: Manage, mentor, and grow the entire development team, fostering a culture of technical excellence and best practices (Testing, DevOps, CI/CD...).Hands-On Development: Act as the primary technical leader and a senior full-stack developer, actively contributing production-grade code and overseeing data engineering pipelines.Data Engineering: Lead the architecture and execution of robust data engineering pipelines required to process, manage, and model complex, high-impact datasets.Collaboration: Serve as the primary liaison between the technical development teams and the AI researchers, ensuring successful integration of research outputs into production-grade systems. Key Requirements: At least 7 years in software development companies, and at least 5 years in management positions. Strong background in Python, AI/ML workflows, deep learning, data modeling, and big data ecosystems. Experience working with complex, real-world datasets and a proven ability to translate abstract research into tangible, scalable software.