Artificial Intelligence Researcher

Shift delivers AI agents that transform insurers' most critical work. By combining deep industry expertise and unmatched data resources, Shift provides proven results that have earned the trust of hundreds of the world's leading insurers. Our insurance-grade AI is accurate, explainable, and secure—empowering human experts to move with unmatched speed, total confidence, and a renewed focus on the people they serve.

     Your browser does not support the video tag.

Our culture is built on innovation, trust, and a drive to transform the insurance industry through our SaaS platform. We come from more than 50 different countries and cultures and together we are creating the future of insurance.

Learn more at www.shift-technology.com

The team

• The Research team plays a key role in Shift’s strategy, developing AI technologies used by insurers and their clients worldwide. We design, evaluate, and industrialize cutting-edge AI systems, with a strong focus on Generative AI and agentic architectures.
• We tackle complex real-world insurance challenges such as fraud detection, liability analysis, subrogation opportunity detection, and decision support across highly heterogeneous and unstructured data including documents, free text, images, and structured claim data.
• Our ambition is to build reliable, production-grade AI systems that can reason over evidence, using tools and skills, and operate safely within critical business workflows.
• As an Artificial Intelligence Researcher, you will join the “Agentic Claims” squad dedicated to developing claim handling agents. These systems support claim handlers by automating tasks and processes, simplify the daily work of claim handlers, and ultimately enhance the experience of the insured.

Your role

• Stay at the forefront of Generative AI and Agentic AI, including LLMs, multimodal models, tool-augmented agents and agentic workflows.
• Design, prototype, and rigorously evaluate specialized AI agents tailored to end-to-end insurance workflows.
• Translate business problems into robust agentic systems, including task decomposition, context and prompt design, tool integration, memory strategies, and advanced evaluation methodologies.
• Take ownership of AI systems from problem formulation and benchmarking to production deployment, monitoring, and continuous improvement.
• Contribute to internal frameworks, benchmarks, and shared tooling to accelerate experimentation and industrialization of agentic workflows.
• Collaborate closely with product, engineering, and data teams to ensure scalability and measurable business impact.