Senior Backend Software Engineer

About ExTrac ExTrac is a decision intelligence company used by governments, defence organisations, financial institutions, and corporates operating in complex, fast-moving environments. Our capabilities fuse curated data sources, domain-specific AI, and deep human expertise to transform information overload into clear, actionable foresight. Our ambition is to become the analytical backbone that organisations rely on when geopolitical uncertainty becomes an opportunity or a strategic risk. More at extrac.ai . The Role We are looking for a Senior Software Engineer to join ExTrac's engineering team to help build and operate the services and pipelines the platform runs on. ExTrac takes a continuously ingested, multi-source corpus and turns it into products analysts use to make decisions under time pressure. You will be responsible for building and running the backend microservices that make that possible: services and databases that expose curated data through APIs, run search and aggregation over large indices, hold application state, and keep the whole thing fast and correct as volume and customer count grow. The work is broad by design. In a single quarter it spans API and service design, search and database performance, long-running data pipelines, cloud infrastructure, and the deployment tooling underneath all of it. You will own services end to end across a Go and Python codebase, working alongside the AI team who build our analytical and agentic features, the frontend team who build the web and mobile interfaces, and the analysts and product managers who define what gets built. What the job involves Service design and delivery Take an ambiguous problem, gather requirements, write a technical design, and ship to production with minimal oversight. Own services end to end, including consolidating or decommissioning what they replace. Contribute to and lead system design and architecture decisions. Design APIs used by both internal teams and customers, and hold them to clear contracts and sensible versioning as the number of consumers grows. Treat the storage layer as a design concern rather than an implementation detail: schema, indexing strategy, and access patterns. Establish clear access patterns and boundaries. Production engineering Develop Go and Python-based microservices to support data collection, processing, and querying. Hold services to production standards for latency, cost, and reliability, with the instrumentation in place to know when they are not meeting them. Build and operate high-throughput data streaming pipelines and work on improving scalability, robustness, and latency. Optimise databases and index performance where it is the constraint on product behaviour. Working with analysts, product, and the ML team Work directly with the analysts who use our products, turning what they hit in practice into changes in the system. Iterate quickly against a live stream of product requests, flagging where they collide with longer-horizo