Senior Software & Platform Engineer – Risk Modeling Platform
Listed on 2026-09-04
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Software Development
DevOps, Python, AI Engineer (Applied/Software), Software Engineer
Senior Software & Platform Engineer – Risk Modeling Platform Job Description
Research shows that women and underrepresented groups often apply only when they meet every requirement. If that sounds like you, we encourage you to rethink it—your unique perspective matters. We’re excited to hear from you!
At our brand-new Shared Business Platform (SBP) in Bucharest, we offer a dynamic environment where career growth is actively supported through internal mobility, globally recognized certifications, and continuous professional development. We value work–life balance, offering flexible work arrangements, and wellbeing initiatives that help you thrive both personally and professionally.
Now, let’s explore this exciting opportunity so that you can be part of our mission.
We are seeking a Senior Software & Platform Engineer – Risk Modeling Platform to join our dynamic Tech team. This is a senior hands‑on engineering role focused on software development, Python, cloud, Dev Ops, and full‑stack platform understanding. The role requires the ability to understand the end‑to‑end platform setup, including infrastructure,cloud deployment, data flows, operational support, and model execution workflows.
The candidate will work across modelling constraints,data integration requirements,and application development, supporting complex risk modelling workflows and contributing to the future integration of the Risk Modeling Platform with strategic data platforms.
ResponsibilitiesKey duties and responsibilities
- Design, efficient, testable, reusable, and reliable code in Python, Docker on a web platform
- Implementation and enhancement of the Front end and Back end of applications responsible for task orchestration
- Implementation and design of the solution on the cloud (mainly Microsoft Azure)
Contribute to applications and platforms that support statistical modelling, analytical workflows, model execution frameworks, and large-scale quantitative computations, and help actuaries optimize models and algorithms
- Working on solutions which uses Linux, Docker, Data Bricks, Jupyter Hub, Postgres, …
Closely work together with IT Technical team to handle automation, incidents, and 3rd level support
- Integration of user-facing elements with server‑side logic
- Work collaboratively in architecting/developing solutions
Work across modelling constraints, data integration requirements, infrastructure, and software development to translate quantitative and business needs into robust technical solutions
Contribute to the future integration of the Risk Modeling Platform with strategic data platforms, working closely with modelling, data integration, architecture, and IT delivery teams
- Working with the team of very skilled Quantitative Developers
- Stay abreast of emerging technologies/industry trends
Required experience & competencies
- 10+ years professional experience building complex, scalable web applications is essential
Proven hands‑on experience designing, building, and operating solutions on cloud platforms, preferably Microsoft Azure, is essential
Quantitative or analytical background, with the ability to understand statistical, actuarial, or risk modelling concepts and collaborate effectively with quantitative modelling teams
- Proficient understanding of Git and Dev Ops standards is essential
- Thorough knowledge of Python and Docker is essential
- Proficient in overall web development and web architecture
Experience working in environments involving statistical models, quantitative analytics, risk modelling platforms, or model execution frameworks is highly valued
- Firm grasp of OOP, FP & SOLID design principles
- Experience working with SCRUM or other Agile methodologies
- Several years in Financial Services industry, preferably Insurance/Reinsurance
- Very good knowledge of English
- Good communication skills with IT and Business
- Team spirit
- Good analytical skills
- Interested in learning new technologies
Knowledge in building big data applications (e.g. Spark, Databricks) and experience using Databricks to support large‑scale model execution and optimization is a strong advantage
Previous experience with .NET/C# is of advantage
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