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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior AI Engineer (Remote) - **Company:** Finom - **Location:** Berlin, Germany (Remote available) - **Experience:** Expert - **Contract:** Temporary contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Fraud Prevention and Detection, Python (Programming Language), Knowledge-Based Systems, NoSQL, Open Source Technology, SQL Databases, Datadog, Pytorch, Large Language Models, Prompt Engineering, Backend, Event Driven Architecture, Containerization, AI Platforms, Kubernetes, HuggingFace, Document Classification, Docker - **Published:** September 6, 2026 - **Apply:** https://www.adzuna.de/details/5872111861 ## About the Role * A strong software engineer with deep Python experience and a track record of shipping production systems * Comfortable across the full lifecycle: prompting, retrieval, experimentation, evaluation, deployment, and production support * Strong at turning ambiguous business problems into robust technical solutions * Product-minded and focused on real user outcomes, not just model outputs * Autonomous, pragmatic, and able to keep momentum without heavy supervision * Clear in communication and comfortable working across functions * Curious, proactive, low-ego, and biased toward action * Someone who actively keeps up with the fast-moving AI landscape and can separate hype from what is actually useful Must-Haves * Proven experience building and deploying AI systems in production * Strong Python and software engineering fundamentals * Hands-on experience with LLM applications, including some of: RAG, tool use, agents, prompt engineering, evals, structured outputs, guardrails, or fine-tuning * Experience integrating AI systems into backend or product workflows * Ability to design meaningful evaluation, monitoring, and continuous improvement loops * Experience with cloud infrastructure and containerized deployments * Strong ownership mindset and ability to work through ambiguity * Actively experiments with new AI models, tools, and agentic patterns, and can evaluate which approaches are worth productionizing * Strong grasp of the fast-moving AI landscape, with the ability to turn relevant advances into practical product and engineering decisions * Fluent English Nice-to-Haves * Experience in fintech, financial services, risk, compliance, or operations-heavy environments * Experience with applied ML beyond LLMs, such as classification, anomaly detection, ranking, or document intelligence * Experience with vector databases, knowledge systems, and retrieval infrastructure * Experience with model benchmarking, experimentation frameworks, and cost or latency optimization at scale * Background in startups or as a founder * Contributions to open-source or visible side projects in AI Example Tech Stack 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 ## Description This role is for someone who can move comfortably from prototype to production: shaping the solution, building the system, measuring quality, and improving it over time. 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. What You Will Be Doing * 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 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 ## Related Videos - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) - [Leveraging Real time data in FSIs](https://www.wearedevelopers.com/videos/806-leveraging-real-time-data-in-fsis) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [Agentic employees in world's most downloaded FinTech app](https://www.wearedevelopers.com/videos/100123-agentic-employees-in-world-s-most-downloaded-fintech-app) - [NoSQL Data Modeling for Front-end Developers](https://www.wearedevelopers.com/videos/297-nosql-data-modeling-for-front-end-developers) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Fully Remote Software Engineer Jobs](https://www.wearedevelopers.com/magazine/447-fully-remote-software-engineer-jobs) - [Dev Digest 137 - AI'm not sure about this](https://www.wearedevelopers.com/magazine/485-dev-digest-137-ai-m-not-sure-about-this) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models)