Principal Scientist, AI Ventures

Principal Scientist, AI Ventures - TR Labs 

This hybrid position is based in Zug, Switzerland. 

Thomson Reuters are seeking a Principal Scientist to lead and architect the applied research behind Thomson Reuters’ AI Ventures incubation unit within TR Labs.

In this innovative role, you will turn frontier techniques — agentic AI and multi-agent systems, orchestration and tool use, retrieval-augmented generation, and knowledge-graph-grounded reasoning — into the products the unit ships, owning the science from hypothesis through production-ready capability. This is a hands-on leadership role for someone who pairs scientific rigor with commercial judgment, knows which approaches from the literature actually work at scale, and builds at startup speed inside a corporate environment. 

About The Role 

• Set and drive the applied-research agenda for the flagship platform and new incubation candidates — designing and executing experiments that answer critical research questions while balancing scientific rigor with business impact. 

• Explore the frontier of agentic AI and multi-agent systems — orchestration, planning, tool use, memory, and evaluation — together with the LLM, RAG, and NLP methods that power autonomous and semi-autonomous workflows, testing what delivers real value in production. 

• Own end-to-end experimentation and development across the research lifecycle — from data ingestion and model selection to agent design and AI-powered applications — guiding work across research, data engineering, and evaluation. 

• Translate practitioner workflows and business objectives in risk, compliance, and fraud into technical requirements and testable research hypotheses. 

• Partner with Engineering to shape an agentic SDLC — embedding AI agents across the software development lifecycle to accelerate experimentation, evaluation, and the path from prototype to production. 

• Champion developer productivity by putting agents to work in day-to-day engineering — using coding agents and AI-assisted workflows to increase the velocity and quality of research and delivery. 

• Be accountable for research deliverables across the unit’s projects, setting the standard for experimental design, reproducibility, and the evaluation of agentic systems. 

• Mentor and coach scientists and engineers, raising the bar on agentic AI, LLM, and NLP best practices. 

About You 

You’re a fit for the role of Principal Scientist, AI Ventures if you have:

• Deep knowledge of agentic AI and multi-agent systems — orchestration, planning, tool use, and memory — with active experimentation across LLMs, RAG, and prompt engineering. 

• Strong grounding in modern NLP methods, with experience using knowledge graphs to provide structured grounding and reasoning over complex, real-world data. 

• Excellent coding skills in Python, proficiency with Git and cloud technologies, and experience writing production-quality code. 

• Demonstrated ability to set a research agenda and design experiments that balance scientific rigor with business impact, translating complex, open-ended problems into successful AI applications — with the judgment to know which techniques from the literature hold up in practice. 

• Experience working with real-world, messy data in commercial or industry contexts — not just clean benchmark datasets. 

• Experience co-designing an agentic SDLC and evaluation processes with engineering, including agent-assisted tooling that increases developer productivity, and moving from prototype to production-ready capability at startup speed. 

• Outstanding communication and analysis skills, with the ability to partner with Product, Engineering, and business stakeholders in an agile way — and to coach and mentor scientists and engineers. 

• Domain familiarity with risk, compliance, fraud, or adjacent enterprise workflows — able to engage credibly with practitioners and executives and learn new domains quickly. 

• Passion for staying ahead of advances in agentic AI, multi-agent systems, LLMs, and generative AI, and the ability to incorporate emerging techniques into the unit’s long-term research direction. 

Preferred Qualifications 

• PhD in a relevant discipline, or a Master’s plus a comparable level of research experience. 

• Demonstrable post-PhD industry experience building NLP / ML / GenAI / agentic AI systems for commercial applications. 

• Experience operating in global, enterprise-scale environments, partnering with engineering, product, and business stakeholders to deliver AI capabilities.