NewsCatcher
Turning the web into a structured database of real world events.
What NewsCatcher does
CatchAll by NewsCatcher is a recall-first web search API built for queries where the results are spread across hundreds or thousands of pages on the web. Instead of returning the top ranked links like traditional search engines, CatchAll retrieves a large candidate set from the web, validates which pages actually match the query, and extracts structured records of real-world events. Developers and data teams use CatchAll to answer “long-list” questions such as tracking regulatory actions, funding rounds, product launches, corporate expansions, or cybersecurity incidents. The output is not just links but clean, deduplicated datasets that can power AI agents, monitoring systems, analytics pipelines, and market intelligence workflows. CatchAll runs on the data infrastructure developed by NewsCatcher, which continuously indexes millions of articles and public web pages across a global network of sources.
1 open role
What the role involves
Functions: Design and implement new data pipelines tailored to a specific project or new product. Continuously improve data pipelines to make them more generic and modular, reducing the effort required for subsequent integrations. Write, optimise and refactor prompts and prompt-related pipelines. Conduct thorough testing and validation of data pipelines to ensure accuracy and consistency of data. Ensure pipelines are optimized for performance, scalability, and reusability to facilitate future projects. Examples of day-to-day tasks We want to support people’s enrichment within the CatchAll Tool. Do research on what is available on the market that can help us enrich data, Double-check open databases, and verify whether there is already an existing solution available within the NewsCatcher’s code base. Plan and design the pipeline. Build a prototype and demo it to the whole team. Proceed to, test on Dev, write test cases around. Deploy on Prod, get feedback and improve. One of the users complained about a job being stuck. Debug the pipeline, try to understand where the problem comes from: promts, code, database. Find the issue and prepare a fix. Test it within the whole pipeline on Dev. Break some pipeline, fix and test again. Deploy on Prod, make clients happy. Prompt responsible for validating results is giving only 50% precision. Review the prompt, review the model. Do some prompt engineering. Realize that “with each new model I feel like LLMs become stupier”. Try another LLM provider, adapt the prompt. Test results, improve the accuracy and create a dataset to prove it. Get 70% precision, wait for compliments. Experience: 3+ years of experience in B2B SaaS as Backend / Software / Data Engineer Strong systems thinker with attention to performance and scalability Comfortable working with both SQL and NoSQL databases Experience shipping LLM-based functionality into production Able to move from prototype → stable, maintainable architecture Must Have Strong Python (including async workloads) Docker & Kubernetes RabbitMQ (or Kafka / PubSub / SNS / ActiveMQ) MongoDB / DynamoDB / Redis Hands-on experience with LLM frameworks We Also Use Elasticsearch/OpenSearch PostgreSQL / MySQL GitLab AWS / GCP / DigitalOcean Jenkins Nice to Have Experience building production AI agents Frontend experience (useful for product UI) Experience in API-first or DaaS companies Compensation and Perks: Competitive salary and equity Up to 24 days of vacation & 16 days of sick leave/holidays (all fully paid) One meeting-free day per week Co-working Budget Training Budget We provide all the necessary equipment to work comfortably and efficiently from home. Yearly company retreats (2025 — Portugal, 2024 — Canary Islands, 2023 — French Alpes)
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Questions and experiences
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Company facts compiled from public sources and last refreshed 9 September 2026. Details change; treat the company’s own site as the authority.