> Markdown version of [/jobs/ext/2503046-senior-ai-engineer](https://www.wearedevelopers.com/jobs/ext/2503046-senior-ai-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior AI Engineer - **Company:** Kayzen - **Location:** Germany (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Clean Code Principles, JavaScript (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Continuous Integration, Distributed Systems, Python (Programming Language), Machine Learning, Routing, Node.Js, Search Technologies, Software Engineering, Systems Integration, TypeScript, Web Applications, Large Language Models, Multi-Agent Systems, Caching, Backend, AngularJS, Front End Software Development, Stream Processing, Data Pipelines, Docker - **Published:** August 28, 2026 - **Apply:** https://de.indeed.com/viewjob?jk=acb2445ee589849a ## About the Role Hands-on AI / LLM Experience * Hands-on experience building and shipping LLM-powered features to production. Practical experience with RAG, embeddings, vector search and/or agentic systems. * Experience with LLM APIs and orchestration patterns; specific frameworks are less important than strong fundamentals. * Good understanding of production LLM concerns such as evaluation, observability, failure modes, cost and latency. * Experience iterating on AI features based on telemetry, evaluation results or user feedback. Strong Software Engineering / Full-Stack Skills * Full-stack product development using Angular, JavaScript/TypeScript, Python, NodeJS etc. is a strong plus. * Strong experience designing APIs, services and production-grade systems. * Ability to write clean, maintainable code and take ownership from implementation through production. * Experience contributing across a product stack and willingness to work on both backend systems and user-facing product functionality. * Comfort working with AWS cloud infrastructure, CI/CD and production environments. Product & Startup Mindset * Bias for shipping, iteration and pragmatic problem solving. * Comfortable with ambiguity and rapid change. * Able to collaborate closely with Product, ML and Engineering stakeholders. * Can discuss trade-offs, challenge requirements constructively and translate AI complexity into practical product solutions. * Thinks in terms of maintainability and reuse rather than one-off demos. Less About * Heavy model training or research. * Designing custom ML algorithms. * Academic optimization work. * Building proofs of concept that never reach production. Nice to Have * Experience with multi-agent systems, tool calling or MCP. * Experience setting up guardrails, moderation and safety checks. * Experience with prompt/context management, routing, caching or fallback strategies. * Experience with Docker and cloud infrastructure (AWS, GCP or Azure). * Experience with modern frontend development and customer-facing web applications. ## Description You will work closely with our Console Engineering, Product and ML teams. Our Engineering organization builds and operates large-scale distributed systems, real-time bidding and budget systems, event and stream processing, data pipelines, and customer-facing products. For this role, the focus is practical: building AI-powered capabilities that become part of the Kayzen Console and are used in real production workflows., We are looking for a Senior AI Engineer who combines strong software engineering fundamentals with hands-on experience shipping LLM-powered products to production. You will design and build AI features for the Kayzen Console and beyond, working across backend services, product-facing functionality, and the LLM layer. This is a hands-on engineering role. We are not looking for a research-focused ML profile or someone who has only experimented with LLMs. This role is ideal for engineers who have already built, shipped, monitored and improved production LLM systems and is comfortable contributing in a full-stack product environment . Responsibilities * Architect, develop, and deploy production-grade LLM capabilities within the Kayzen Console * Build backend services, APIs, and integrations that connect AI capabilities with our product. * Contribute to product-facing and full-stack functionality where needed. * Implement production patterns for LLMs, RAG, embeddings, agents, and tool calling. * Build reusable components and abstractions where they improve engineering velocity and consistency. * Set up and improve evaluation, observability, monitoring, and feedback loops for AI features. * Monitor and optimize quality, latency, reliability, and inference cost. * Troubleshoot production issues and iterate based on telemetry and user feedback. * Work closely with Product, ML and Engineering to translate product problems into pragmatic AI solutions. * Prototype quickly, validate ideas, and turn successful experiments into maintainable production systems. ## Related Videos - [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) - [HTTP headers that make your website go faster](https://www.wearedevelopers.com/videos/1676-http-headers-that-make-your-website-go-faster) - [How to Avoid LLM Pitfalls - Mete Atamel and Guillaume Laforge](https://www.wearedevelopers.com/videos/1328-how-to-avoid-llm-pitfalls-mete-atamel-and-guillaume-laforge) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) - [LLMs in the wild: Building an AI agent that survives production](https://www.wearedevelopers.com/videos/100319-llms-in-the-wild-building-an-ai-agent-that-survives-production) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [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) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)