Founding Member, Data Scientist / AI Engineer

About Cadensys

Cadensys is founded by ex-Revolut and Trade Republic executives and backed by leading global VCs. We are on a mission to revolutionise the way businesses are operated. Cadensys solves the problems caused by scattered tools and disjointed workflows by unifying data and coordinating agents.

We are building an operating system orchestrating work between human workers and AI agents, across all tools and company-wide. By learning how humans make decisions and take actions, we enhance their effectiveness by allowing them to be problem solvers and not tool operators.

We are looking for a Data Scientist / AI Engineer committed to driving change in the way people work and with a desire to innovate by creating data-driven AI-solutions supporting process mining, mapping, monitoring and design.

Role Overview

As a Data Scientist / AI Engineer, you will play a key role in developing cutting-edge AI solutions, designing and implementing systems that integrate AI into real-world business applications, focusing on agentic applications for information and data retrieval and summarisation, process mining and automation. As one of the first hires, you will over time build and guide the AI team, contribute to technical direction, and collaborate with cross-functional teams to deliver powerful AI-driven automation solutions.

Key Responsibilities

• Lead the development of AI solutions to automate business processes, ensuring high performance, scalability, and reliability.
• Build advanced agentic LLM/RAG systems, optimising performance and cost, making decisions on mixing and matching foundation, fine-tuned, and home-build models to achieve best-in-class performance of the product.
• Work with product engineering teams to understand business requirements and translate them into AI-powered solutions.
• Provide technical leadership, guiding and mentoring other engineers in best practices and coding standards.

Requirements

• Experience in deep learning with natural language processing.
• Strong understanding of large language models and grounding techniques.
• Experience deploying and monitoring AI models in production and at scale.
• Strong knowledge of data science in general,
• Big picture thinking to design and implement complex AI algorithms solving business problems.
• Excellent communication and collaboration skills to partner with in-house product teams and clients.

Nice to have

• A master's or PhD degree in a quantitative discipline.
• Experience with knowledge graph / ontology construction from structured and unstructured data and its use for information retrieval.
• Experience interfacing with disparate remote sources of structured and unstructured data (API, data warehouse, and file based).