Backend Software Engineer (Python)

About Signal Ocean: Signal Ocean is the technology arm of the Signal Group, providing market-leading advanced machine learning and AI-driven intelligence to shipping and commodities professionals worldwide. Our platform delivers tailored, exclusive insights through web, mobile, and API interfaces, enabling clients to make faster, better-informed commercial decisions. Signal Ocean has recently acquired AXSMarine, a business with over 25 years of experience in the freight and commodities space - and is actively integrating the two companies. The combined business now offers the most comprehensive suite of freight market intelligence available, and we are actively building the team to realise the full potential of the integration. About the role As the Signal Ocean Platform continues to grow, we’re expanding our engineering team. We’re looking for a Software Engineer capable of building and maintaining scalable back-end data services (primarily in Python) within the Modelling & Data Services team. Signal’s Software Engineers work closely with data science, design, product, and business analysis professionals to develop robust solutions for the highly entrepreneurial domain of shipping. Technology stack: We build cloud solutions using C#, .NET Core, Typescript, React, MSSQL Server, Azure, Python, MongoDB, Redis, Docker, Kubernetes, Grafana and more. We also offer the opportunity to work on complex architectures and technology stacks, as well as a global AI-powered tech product vision, supported by the use of multiple AI tools and accelerators. We use Agile to organize our teams and would love to onboard people who can contribute across product discovery, delivery, optimization, QA, DevOps, and Continuous Integration. Key Responsibilities: Design and develop efficient, production-ready backend services – Transform prototypes and specifications into robust, scalable Python microservices that meet quality standards, performance requirements, and monitoring best practices Collaborate with data scientists and analysts – Act as a technical implementation partner, taking research prototypes and converting them into production-grade code with proper testing, error handling, and observability Maintain existing microservices – Investigate production issues, implement fixes, and enhance monitoring capabilities across the freight solutions backend ecosystem Ensure code quality and best practices – Write well-tested, documented code following software engineering standards; conduct code reviews and establish quality benchmarks for the team