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Mentor Talent Acquisition is seeking a Backend Engineer in Vienna to design, build and scale backend services using Python. You will work on API development, data pipelines and AI-powered product features, collaborating with product and frontend teams in a cross‑functional setup.
The role emphasizes strong backend fundamentals with potential growth into data engineering and AI product work, supported by an international team and modern tech stack.
Location: Vienna, Austria
Remote option available with quarterly office visits for one week in Vienna.
This 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 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.
The 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:
Build the future of AI‑powered finance.