Senior AI engineer About Accelex The private markets ecosystem is awash with unstructured content in the form of PDFs and other documents carrying difficult-to-access investment information. Many firms struggle with highly manual data extraction, sharing and reporting processes that are costly, inefficient and time-consuming. Powered by cutting-edge data science, artificial intelligence and machine learning techniques, Accelex streamlines the extraction, analysis and reporting of critical private investment data. Using dynamic data acquisition algorithms, our next-generation SaaS platform brings automation, scale and auditability to demanding workflows. As investors seek greater transparency into funds and their underlying assets, the Accelex solution automates the extraction of unstructured performance and transaction data from a wide range of private investment documents. The role Accelex is looking to hire a Senior AI Engineer to the data science team. The candidate should have experience in developing and bringing new technologies to production. As a Senior AI Engineer an excellent knowledge of Python is essential. Accelex' s document intelligence stack uses a variety of techniques including LLMs, NLP and machine vision. Increasingly, Accelex is focused on building solutions on top of LLMs, for which software and data engineering skills are as or more important than a theoretical knowledge of the underlying data science techniques. The role involve building and maintaining AI workflows, RAG pipelines and supporting our existing stack of single-task, discriminative models. We have a modern cloud-native tech-stack running on AWS and offer the right candidate an excellent opportunity to work in a dynamic startup environment using cutting-edge techniques. Responsibilities and requirements 5 years experience Excellent knowledge of Python Familiarity with RAG pipelines and deploying LLM-based solutions Familiarity with building AI workflows and prompt chains to solve business problems Strong focus on testing, observability and production monitoring Defining data pipelines and developing microservices for deployment on AWS lambda or Kubernetes Work with engineering & product teams to bring commercial solutions for clients to production Consider and manage information security risk in the execution of all activities, and support the organization in its information security obligations Qualifications A PhD, Masters degree or Bachelors degree in machine learning or equivalent experience in quantitative field (e.g. Statistics, Mathematics, Computer Science, Engineering) Company benefits : Group Company Healthcare Plan Group Retirement Plan If you're passionate about building and deploying AI solutions and excited to work for an innovative technology start-up, we'd love to hear from you