We are a news intelligence company. We aggregate and process content from 85,000 news sources in 42 languages in real time. Our platform is used by communications teams, investors, government press offices, and corporate affairs functions who need to understand what is being written about topics, companies, and people — and why it matters. The NLP stack is the product. Topic classification, entity recognition, sentiment analysis, narrative clustering, and influence scoring — these are not features in a platform, they are the platform. We are hiring a contract NLP Engineer for a 9-month engagement to work on two specific improvements to our English-language pipeline: improving entity disambiguation in financial and political contexts where homonymous entities are common, and extending our narrative clustering model to handle emerging topics that were not represented in the training data. The work is applied and fast-moving. Our training data is real news, which means it is noisy, politically complex, and occasionally adversarial. We expect the engineer we hire to care about those properties, not just the benchmark numbers.