Artificial Intelligence Engineer

Senior R&D Data / Full Stack Engineer Location: Remote Engagement: Contract (CTH possible for the right candidate) Experience Level: Senior (5+ years) About the Role We are seeking a Senior-level Data / Full Stack Engineer to support Research & Development (R&D) initiatives within a large enterprise environment. This role will be highly hands-on and focused on solving complex, real-world R&D challenges through data analysis, optimization, and scalable technical solutions. While the primary focus will center around R&D data initiatives — including experimentation, modeling, and innovation enablement — this role will maintain collaboration with Supply Chain teams to ensure downstream operational alignment and feasibility. Key Responsibilities • Work day-to-day on R&D data initiatives, supporting innovation, experimentation, and product/process development efforts. • Analyze and optimize R&D datasets to improve insights, efficiency, and decision-making. • Design, build, and support data-driven applications and technical solutions that enable research teams and business stakeholders. • Partner with R&D, engineering, and supply chain stakeholders to translate business and technical challenges into scalable solutions. • Contribute to modeling, optimization, and analytical efforts tied to research outputs and operational scalability. • Support large-scale enterprise systems and data platforms that integrate R&D and supply chain data. Required Skills & Experience • 5+ years of professional experience in a data engineering, data science, or full stack engineering role. • At least 3 years of experience supporting complex data-driven initiatives in R&D, manufacturing, supply chain, or similarly analytical environments. • Strong hands-on experience with: • SQL • Python • Palantir • Databricks • Experience working within large enterprise environments. • Strong analytical, modeling, and problem-solving skills. • Ability to operate independently in a remote environment. Nice to Have • Experience applying AI or machine learning to R&D, product development, or operational optimization use cases. • Exposure to supply chain data integration or operationalization of research outputs. • Experience with optimization frameworks or advanced analytics in enterprise environments.