Descripción de la oferta
Location: Vienna, AustriaRemote option available with quarterly office visits for one week in Vienna.About the companyThis is one of Austria's most exciting scale-ups, having recently raised more than €15 million. The team is ambitious and international, working on an exciting AI-first product with the opportunity to work with modern technologies while helping shape the future of finance.The company empowers business leaders to make better strategic decisions in financial management, reporting and planning. Its mission is to help companies connect, analyze, forecast and automate all their financial data in one place.It is backed by renowned investors, including Atlantic Labs, CommerzVentures and founders of Wefox, and is building the next generation of AI-native finance software.The MissionThe company is looking for a Backend Engineer to help connect its backend and data infrastructure with LLM-powered features, agents and self-service capabilities. This role is primarily backend-focused: designing and building scalable services, APIs and business logic using Python.Experience with data engineering (ETL/ELT pipelines, AWS data services, dimensional modelling) is a strong advantage and something the team will actively help develop further, but it is not a requirement. What matters most is strong backend engineering fundamentals combined with curiosity and a genuine interest in eventually working across data and AI product engineering as well. Backend and Data Engineering work closely together at the company, and engineers benefit from understanding both worlds. Someone who comes in strong on backend will be supported in growing into data engineering over time.ResponsibilitiesBackend EngineeringDesign, build and maintain scalable backend services using Python.Develop new product features and reusable backend architectures.Build reliable APIs, integrations and business logic.Improve system performance, reliability, security and maintainability.Identify technical bottlenecks and continuously improve the platform.Participate in architecture discussions and technical decision-making.Expose existing system capabilities through clear, secure and well-structured interfaces.AI Product & Agent EngineeringBuild production-ready product features powered by large language models.Integrate LLMs into existing products, workflows, backend services and data systems.Expose complex business logic and system capabilities to AI models through structured APIs, tools and agent interfaces.Design reliable AI workflows using tool calling, structured outputs, retrieval and multi-step agent processes.Contribute to prompt design, context management and model selection.Cross-functional CollaborationCollaborate closely with Product, Frontend and other engineers.Translate product requirements into robust technical solutions.Write clean, maintainable, well-tested and well-documented code.Share knowledge across teams and continuously improve engineering standards.Take ownership from problem definition through implementation and production operation.SkillsCore SkillsStrong Python programming skills.Experience building and operating production software.Good understanding of object-oriented programming and software design principles.Solid SQL knowledge.Experience with AWS.Experience designing or consuming REST APIs.Experience with Git and CI/CD.Strong analytical and problem-solving skills.Ability to work independently and take ownership.Nice to HaveExperience with ETL or ELT pipelines.Experience with dimensional data modelling or Medallion Architecture.Experience with Docker and Kubernetes.Familiarity with GraphQL or Terraform / Infrastructure as Code.Experience with ClickHouse, Redshift or other analytical databases.Experience building LLM-backed product features, RAG, embeddings or agent frameworks (e.g. MCP).What Matters MostThe ideal candidate is curious, pragmatic and eager to learn. Being strong in both backend and data engineering from day one isn't required - what matters most is bringing strong backend fundamentals and motivation to grow.The most important factors, above specific tech stack breadth, are:Character and ownershipCuriosity and a strong willingness to learnPragmatic problem-solvingProduct thinkingA strong quality mindsetPassion for building useful productsWhat's On OfferJoin one of Europe's most exciting AI-first finance start-ups.Take significant ownership and responsibility from day one.Grow from a strong backend foundation into data and AI product engineering.Learn from experienced engineers and continuously broaden your technical skill set.Shape the architecture of a modern AI-native finance platform.Work with a highly motivated international team.Use modern technologies and engineering practices.Office in the heart of Vienna, or remote with quarterly office weeks in Vienna.Competitive compensation, equity participation and meaningful opportunities for personal and professional growth.Build the future of AI-powered finance.
