> Markdown version of [/jobs/ext/1627812-ai-platform-engineer](https://www.wearedevelopers.com/jobs/ext/1627812-ai-platform-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). --- # AI Platform Engineer - **Company:** 100 - Hellmann Worldwide Logistics SE & Co. KG - **Location:** Osnabrück, Germany - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Audit Trail, Information Engineering, Python (Programming Language), Operational Data Store, Software Engineering, Large Language Models, Snowflake, AI Platforms, Kubernetes, Enterprise Integration, Virtual Agents - **Published:** July 16, 2026 - **Apply:** https://de.indeed.com/viewjob?jk=33cc8da880f0d317 ## About the Role * Experience as a software or, ideally, a platform engineer * Hands-on experience with AWS and in data engineering, ideally with Snowflake * Have run LLM-based applications in production, or closely supported doing so * An understanding of agents: tool use, context engineering, evaluation, observability * High agency and the ability to make decisions and explain your reasoning clearly * You use AI daily in your own work ## Description Self-service for business units. Non-engineers in the product areas should be able to build their own dashboards and tools-with AI as a tool and a secure runtime environment provided by us. AI in engineering. We're fundamentally changing our software engineering processes: shift left, agentic engineering, spec-driven development. Agentic AI in the core business. Perhaps the biggest opportunity of all: agents in our operational core processes, as a core way we create value and scale. In doing so, we're entering uncharted territory, and we're aware that no one has a ready-made blueprint for this. What matters here is our ambition: this isn't about becoming a bit more efficient here and there-we're convinced that AI changes the way this company works. And we're building our platform around that from the ground up., You'll be part of the AI Platform Team, which is currently taking shape. It's emerging within our DXP team (Developer Experience Platform), which has already built and operates a Kubernetes-based Internal Developer Platform. The new team is deliberately kept small, senior-led, and close to the existing platform expertise. You'll build the path that takes AI into production here: * From prototype to productive application. You build the bridge from "sketched out with Claude in Python" to "running-observed and secured-in operations." * Selecting and integrating components. LLM gateway, container runtime, workflow and agent orchestration, observability, cost tracking. As a team, not alone. * Snowflake as the context layer. You'll make Snowflake the home for our agents' data-for operational data, and in the longer term for ontological knowledge as well. * Backend integration. Via API and MCP, secured through gateways, and where it makes sense, as a CLI. * Making agents observable. Prompt, tool-use, and cost telemetry end to end, evals as part of the lifecycle, lineage from the user action through the model call to the effect in the core system. * Security as a platform feature. Machine identities and permissions for agents, guardrails against prompt injection, clean secret management, audit trails. ## Related Videos - [AI-Augmented DevOps with Platform Engineering](https://www.wearedevelopers.com/videos/1614-ai-augmented-devops-with-platform-engineering) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [Resilient by Design: Building Robust Architectures in High-Stakes Financial Systems](https://www.wearedevelopers.com/videos/2106-resilient-by-design-building-robust-architectures-in-high-stakes-financial-systems) - [Understanding Kubernetes in a visual way](https://www.wearedevelopers.com/videos/100085-understanding-kubernetes-in-a-visual-way) - [The Private AI Platform: Why Agentic Apps Need a Private Application Platform](https://www.wearedevelopers.com/videos/100162-the-private-ai-platform-why-agentic-apps-need-a-private-application-platform) - [Hacking AI at the Edge of the Indian Ocean](https://www.wearedevelopers.com/videos/100177-hacking-ai-at-the-edge-of-the-indian-ocean) ## 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 – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere) - [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) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)