AI Engineer - Algorithm Team

Our Algorithms group is a highly multidisciplinary group at the core of our data processing and detection capabilities , integrating physics, signal processing, classical algorithms, and AI models to meet our unique requirements. As we scale, we are increasingly leveraging Large Language Models (LLMs) and agentic AI systems to accelerate our research, automate complex workflows , and unlock new capabilities across the company. Job description As an AI Engineer at Exodigo, you will join a fast-moving, highly technical team that works at the intersection of computer vision, deep learning, and modern AI . You will be the driving force behind our LLM and agentic AI efforts - exploring, evaluating, and deploying the latest research and tooling in this rapidly evolving space, and shaping how we apply it across the organization to turn cutting-edge ideas into production-ready tools and agents. You will design and build LLM-powered applications, agentic workflows, and internal tools that empower our algorithms, mapping, and engineering teams to move faster and operate at greater scale. Collaboration is central to the role, you will work closely with researchers, engineers, and domain experts to identify high-impact opportunities , prototype quickly, and integrate reliable AI systems into real-world products. Key Responsibilities • Design, build, and iterate on LLM-powered applications , including retrieval-augmented generation (RAG) systems, agents, and fine-tuned models tailored to Exodigo's unique data and workflows. • Develop agentic workflows that automate complex, multi-step tasks across research, data analysis, and engineering pipelines. • Build internal tools and assistants that empower algorithm researchers, mapping experts, and engineers to work faster and more effectively. • Evaluate and integrate the latest foundation models, frameworks, and techniques (e.g., prompt engineering, fine-tuning, tool use, multi-agent orchestration), keeping pace with rapid advances in the field. • Design robust evaluation methodologies to measure quality, reliability, and safety of LLM-based systems. • Collaborate closely with the Algorithms, Mapping, and Software teams to identify high-impact opportunities and transition prototypes into reliable, production-grade systems.