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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Software Engineer 1 (MLOps) - **Company:** Aioi Nissay Dowa Europe - **Location:** King's Sutton, UK - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Clean Code Principles, Artificial Intelligence, Amazon Web Services, Cloud Computing, Continuous Integration, Information Engineering, Data Governance, Data Security, Python (Programming Language), NumPy, Commercial Software, Large Language Models, Code Structure, Pandas, Containerization, Core Data, Scikit Learn, Kubernetes, Data Analytics, Machine Learning Operations, Software Version Control, Data Pipelines - **Published:** July 26, 2026 - **Apply:** https://www.apply4u.co.uk/jobs/x/42002476/ ## About the Role effectively across a broad stack (compute, storage, serving, tooling) rather than specialising in a single area. * Navigating the balance between moving quickly to support research timelines and maintaining engineering rigor and security standards. * Growing technical skills and confidence in ML infrastructure through hands-on work, in an environment that values learning. * Balancing innovation in generative AI with requirements around privacy, data sovereignty, security and operational trust. * Ensuring that project outputs contribute not only to immediate delivery but also to longer-term reusable capability within the Lab. Knowledge, Experience and Qualifications Essential * Extensive commercial software experience, with a track record of delivering working, maintainable code in a team setting. * Solid Python skills, including core data and ML-adjacent libraries (pandas, numpy, scikit-learn) and good instincts around code structure, testing and packaging. * Experience with cloud infrastructure at a practical level: deploying services, managing storage, working with access controls. * Familiarity with Kubernetes and Helm. * AWS experience preferred, strong experience with another provider considered. * Experience with ML infrastructure or data engineering: training pipelines, model serving, experiment tracking, or data pipelines. * Comfortable with CI/CD pipelines, version control, and containerisation as everyday tools, not just concepts. * Able to engage with technically complex and ambiguous problems, ask good clarifying questions, research and develop new skills, and work iteratively toward solutions. * Good communication skills: can explain what they've built, justify their decisions, explain what trade-offs they made, and flag up what they're unsure about. Desirable * Exposure to LLM serving or fine-tuning workflows, even at small scale or in personal projects. *, Understanding of data governance or security ## Description Job DescriptionWe're Aioi R&D Lab - an AI tech hub in one of the fastest-growing insurance companies. We research and develop AI systems that catapult insurance from a slow-moving, traditional past into a data-driven, technology-lead and society-defining future. We're looking for dynamic, driven professionals like you to help evolve our business in new directions. You'll need first-class credentials and a proactive attitude to help us drive the change the underpins our mission. As a Senior Software Engineer 1 (ML Ops) you'll be contributing to the design, build, and operation of cloud infrastructure supporting a privacy-preserving AI research programme, working under the direction of the Technical Lead. You will help deliver model hosting and training infrastructure, secure data storage, and agentic development tooling - the foundations the programme's research tracks depend on. If you'd like to be part of our brighter future, and share in our success, we'd love to hear from you. Responsibilities * Contribute to the design, build, and operation of cloud infrastructure supporting a privacy-preserving AI research programme, working under the direction of the Technical Lead. * Help deliver model hosting and training infrastructure, secure data storage, and agentic development tooling - the foundations the programme's research tracks depend on. * Write clean, well-tested, maintainable code and contribute to shared engineering standards, CI/CD pipelines, and documentation. * Support integration of infrastructure components with partner environments and research workflows, troubleshooting issues as they arise. * Engage actively with technical trade-offs, ask good questions, and learn quickly as tool choices and requirements evolve throughout the programme. * Working within a multi-partner programme where requirements evolve and final tool choices are not fixed from day one. * Building robust infrastructure that research teams can depend on. * Contributing ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Vectorize all the things! Using linear algebra and NumPy to make your Python code lightning fast.](https://www.wearedevelopers.com/videos/562-vectorize-all-the-things-using-linear-algebra-and-numpy-to-make-your-python-code-lightning-fast) - [Advanced Typing in TypeScript](https://www.wearedevelopers.com/videos/496-advanced-typing-in-typescript) - [MLOps - What’s the deal behind it?](https://www.wearedevelopers.com/videos/392-mlops-what-s-the-deal-behind-it) - [Building Multi-Tenant ASP.NET Core Applications: Best Practices and Real-World Solutions](https://www.wearedevelopers.com/videos/1552-building-multi-tenant-asp-net-core-applications-best-practices-and-real-world-solutions) - [The state of MLOps - machine learning in production at enterprise scale](https://www.wearedevelopers.com/videos/369-the-state-of-mlops-machine-learning-in-production-at-enterprise-scale) ## Related Articles - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift)