Alle Startup-Jobs

Introduction

Yttrium is a growth equity firm specialized in B2B technology. We partner with management teams of high-growth businesses and help them scale into global digital leaders. We currently manage over EUR 750m across more than 20 portfolio companies, supported by a team of 20+ investment professionals and Advisory Partners based in Frankfurt, Munich and London.

Data and AI are central to how we source, diligence and monitor investments. Over the past two years we have built “Scale”, our in-house data and AI platform: a data warehouse with ingestion pipelines, a suite of agentic workflows and MCP servers, and two full-stack applications used day-to-day by the investment team. The foundation is live and in production; the roadmap ahead is substantial. We are now looking for a Junior Data & AI Engineer to join our Frankfurt office and help take the platform to the next stage.

The role

You will join a two-person data and AI team as the second hire, working directly with our in-house data scientist who leads the data and AI workstream and has built the current version of Scale. Beyond the core team, you will work closely with a Manager, a Principal and two Partners from the investment team, who are actively involved in shaping priorities, reviewing work and using what we build day-to-day. The team is based in Frankfurt.

On day one you will be plugged into a real, production platform with established conventions, agentic workflows and two full-stack web applications. Your job is to help extend it: new data sources, new agents, new features and everything in between. This is an unusually broad role for a junior hire. You will work across the full stack, ship production code used by investment professionals within your first weeks, and learn from and ship alongside the data scientist who has been building the platform.

The role is not purely technical. A meaningful part of the job is helping the rest of the firm get more out of data and AI, by rolling out tools, acting as a sparring partner for the investment team on technical due diligences and exchanging learnings with portfolio companies on AI and data topics.

What you will do

• Build and maintain data pipelines ingesting internal and external sources into our data warehouse and make the data accessible to the team and AI agents
• Extend our internal MCP servers and Langdock-based agentic workflows to support deal sourcing, screening, due diligence and portfolio monitoring
• Contribute to our web applications across backend and frontend
• Work closely with investment professionals to translate business questions into data products and ship MVPs in short build cycles, iterating with our data scientist and the broader team
• Champion the adoption of AI tooling across the firm, for example Claude and its Cowork mode, Langdock (our AI workspace) and other best‑in‑class tools, through hands‑on onboarding, internal playbooks and ongoing support for colleagues
• Act as a technical sparring partner for the investment team on due diligences in AI, data infrastructure and adjacent sectors, helping to stress‑test theses, technical claims and product architectures
• Exchange learnings on AI and data topics with portfolio companies through informal exchanges and round tables

Our stack

• Data platform: Python, Dagster, dbt, BigQuery and integrations with internal business apps, external web data and AI agent infrastructure
• Applications: One internal and one external‑facing app with FastAPI backends and TypeScript/React frontends deployed via Cloud Run
• Workflow: AI‑assisted and PR‑based development, CI/CD via GitHub Actions and Cloud Build

What we are looking for

We are not looking for someone who already knows every tool in the stack. We are looking for someone who is motivated to learn fast, take ownership and build at the intersection of data, AI and investment.

Required

• Completed academic degree in Computer Science, Data Science, Engineering, Mathematics or a related quantitative field, or in Economics or a similar field if combined with significant coding exposure (side projects, thesis, research, open‑source work); strong academic track record
• First hands‑on experience with data engineering: Python, SQL and Git, gained through internships, working‑student roles, a thesis or substantial personal projects
• First exposure to finance, either through internships, working‑student positions or deep personal interest in consulting, investment banking, private equity, venture capital or growth equity
• Agentic coding: power‑user of Cursor, Claude Code, Codex or similar, with opinions on how to use them well in a real codebase
• Practical experience building with LLMs and agents: you have used model APIs (OpenAI, Anthropic or similar) and built at least one non‑trivial agentic workflow
• Fluent in English and German; comfortable communicating directly with investment professionals and portfolio companies in both languages
• Self‑starter mindset: able to drive projects forward independently once the objective is clear, while asking for context and feedback when needed

Nice to have

• Some experience with Docker and TypeScript/React frontend development
• First touch points with a cloud native stack, ideally Google Cloud Platform
• Previous work experience in start‑ups, scale‑ups or technology‑focused investment teams
• Exposure to the PE/VC workflow: sourcing, due diligence, portfolio monitoring and reporting

What we offer

• A rare opportunity to help build the data and AI function of a leading European growth equity firm from an early stage, with direct visibility to partners and the investment team
• Ownership over meaningful parts of the stack, across pipelines, agents, backends and frontends, in a codebase small enough to fully understand and shape
• A modern engineering environment with AI‑assisted development as a first‑class part of the workflow
• Frankfurt‑based role with a collaborative, entrepreneurial team culture and close daily collaboration with the investment team
• Strong personal development trajectory and the opportunity to build a professional network across the European PE/VC and B2B technology ecosystem through regular exposure to investors, founders and portfolio companies
• Competitive compensation and development through courses, conferences and certifications