Senior Applied AI Researcher, Vice President
About this roleWe are looking for a Senior Applied AI Researcher (6+ years of experience) to join our data science team working on advanced AI-driven solutions. This is primarily an individual contributor role, with responsibility for owning end-to-end ownership of complex modelling / AI problem areas and technical ownership of AI capabilities critical to the product. The role focuses on the research, prototyping, evaluation, and improvement of AI solutions, with hands-on work across LLM-based systems, including agent-style workflows and retrieval-augmented generation (RAG) where appropriate. You will work end-to-end: collaborating with stakeholders and product managers to define problems, building and validating prototypes, presenting findings to diverse audiences, and supporting engineering teams during implementation and production rollout. Key Responsibilities End-to-end AI solution ownership Own AI projects or functional modules from problem definition through prototype validation and production support. Partner with product managers and business stakeholders to translate real-world problems into clearly scoped data science and AI initiatives. Independently plan and execute research, experimentation, and iteration cycles in ambiguous problem spaces. Design AI solutions with a system‑level perspective, ensuring scalability, maintainability, and long‑term sustainability. Applied AI, LLMs, and agentic systems Design and prototype LLM-powered solutions, including RAG-based systems and agent-like workflows (e.g. tool use, orchestration, multi-step reasoning). Contribute to defining system behavior, scope, and constraints, with attention to quality, robustness, and operational considerations. Stay current with emerging AI techniques and apply them pragmatically to solve business problems. Evaluation, validation, and performance improvement Build and maintain evaluation frameworks to assess AI system performance (accuracy, reliability, relevance, robustness, safety). Develop quantitative and qualitative metrics, benchmarks, and testing approaches to validate prototypes and track improvements. Analyze existing solutions to identify gaps and drive continuous, data-driven performance enhancements. Collaboration and communication Work closely with data scientists, engineers, and product teams to ensure smooth transition from prototype to production. Clearly communicate methods, assumptions, results, and limitations to technical and non-technical audiences. Support engineering teams during implementation by clarifying evaluation criteria, edge cases, and expected system behavior. Serve as a technical authority and actively mentor junior data scientists, shaping best practices in expe...