Stellenbeschreibung
- We are looking for a Senior AI Engineer to design, build, and operate AI systems that solve real business problems across Finom
- You will work on high-impact initiatives across onboarding, customer support, AI accounting, fraud and risk workflows, document understanding, internal automation, and agentic systems used by multiple teams
- This is not a pure research role. It is a hands-on engineering role focused on delivering production-grade AI capabilities that create clear value for customers and the business
- Build and ship AI-powered product and internal solutions using LLMs, RAG, tool calling, workflows, and agentic patterns
- Own AI systems end-to-end: problem framing, architecture, implementation, evaluation, deployment, monitoring, and iteration
- Partner closely with solution managers, domain teams, and engineers to integrate AI into real workflows rather than isolated demos
- Design quality and evaluation frameworks for AI systems, including offline evals, online signals, failure analysis, and continuous improvement loops
- Develop scalable and reliable inference pipelines with strong attention to latency, cost, security, and observability
- Work on use cases such as onboarding, customer care, transaction and document classification, knowledge assistants, fraud detection, and operational automation
- Contribute to AI platform and tooling decisions that improve reuse, speed, and consistency across teams
- Challenge assumptions, propose better approaches, and help shape the roadmap rather than only execute tickets
- Experiment boldly, learn quickly from failures, and turn insights into stronger systems and better practices
What Success Looks Like:
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In your first 6 to 12 months, you will:
- Become fully embedded in the team and business domains you support
- Deliver at least one significant AI capability into production
- Generate visible impact through revenue uplift, cost savings, productivity gains, or risk reduction
- Raise the technical bar for how Finom builds, evaluates, and operates AI systems
- Help other teams adopt AI more effectively through strong engineering practice and pragmatic guidance
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You do not need experience with every item, but this role will likely involve technologies such as:
- Languages: Python, SQL, noSQL
- LLM / AI: OpenAI, Anthropic, LangGraph, Hugging Face, Ollama, PyTorch, OpenClaw
- Patterns: RAG, tool calling, agent workflows, eval pipelines
- Infrastructure: Docker, Kubernetes, AWS / GCP / Azure
- Data / Platform: Vector databases, event-driven systems, APIs, observability tooling
