• Lead the design and architecture of scalable full-stack solutions aligned with product requirements • Own the architecture of core subscription and membership systems, including billing correctness, lifecycle state management, plan changes, cancellations, and workflow orchestration across commerce, pharmacy, and fulfillment • Partner closely with engineering teams across commerce, clinical care, pharmacy, and fulfillment to drive cross-functional technical initiatives and ensure platform decisions scale across the organization • Provide mentorship on best practices, design patterns, and coding standards • Advocate for team technical needs within the broader engineering organization • Participate in product discovery and validation through prototypes and experiments • Partner with product and design to ensure platform capabilities support an intuitive end-to-end customer experience • Drive strategic technical decisions to improve security, scalability, and performance • Break down complex projects into actionable tasks • Establish and enforce consistent coding and testing standards • Initiate efforts to reduce technical debt and enhance workflow efficiency • Implement tools and processes for monitoring, incident response, and performance optimization • Implement analytics and monitoring to demonstrate how engineering solutions directly impact key customer activation and reactivation KPIs • Analyze metrics and user feedback to continuously improve the platform • Maintain thorough technical documentation • Conduct code reviews and facilitate knowledge-sharing initiatives

• Build and optimize data pipelines (batch and streaming). • Extracting, analyzing and modeling rich and diverse datasets of structured and unstructured data. • Design software that is easily testable and maintainable. • Support in setting data strategies and our vision. • Keep track of emerging technologies and trends in the Data Engineering world, incorporating modern tooling and best practices at Craft. • Work on extendable data processing systems that allows to add and scale pipelines. • Apply machine learning techniques such as anomaly detection, clustering, regression classification, and summarization to extract value from our data sets. • Leverage AI-powered development tools (e.g. Cursor) to accelerate development, refactoring, and code generation.

Role Description - Du entwickelst und betreibst unsere souveräne LLM-Plattform inklusive OpenAI-kompatiblem Gateway, Modell-Serving und GPU-Infrastruktur. - Du implementierst kundenspezifische Wissensanbindungen (RAG) mit Vector-Datenbanken, Embeddings und Reranking. - Du stellst Kostenkontrolle, Mandantentrennung, Datenschutz und Guardrails sicher. - Du etablierst Monitoring und Observability für Performance, Qualität und Nutzung der KI-Dienste. - Du betreibst und entwickelst unsere containerbasierte Plattform auf Basis von Docker, Coolify und Kubernetes weiter. - Du automatisierst Deployments und verantwortest CI/CD-Prozesse für unsere Eigenentwicklungen. - Du betreust unsere Linux-, Cloud- und Datenbank-Infrastruktur und sorgst für Stabilität, Sicherheit und Verfügbarkeit. - Du baust Monitoring-, Logging- und Alerting-Lösungen auf und entwickelst diese weiter. - Du gestaltest die Architektur unserer Plattform- und KI-Services aktiv mit. - Du etablierst Infrastructure as Code und standardisierte Deployment-Prozesse. - Du sorgst für datenschutzkonforme und mandantensichere Betriebsmodelle. - Du dokumentierst Lösungen, teilst Wissen im Team und evaluierst neue Technologien im Bereich Platform Engineering und KI. Qualifications - Abgeschlossenes Studium der (Wirtschafts-) Informatik oder eine vergleichbare Qualifikation. - Mehrjährige Erfahrung im DevOps-, Plattform-Engineering- oder Cloud-/Infrastruktur-Umfeld. - Fundierte Praxiserfahrung im Betrieb containerbasierter Anwendungen und moderner Plattformen. - Erfahrung im Aufbau und produktiven Betrieb von LLM- und KI-Diensten, idealerweise in selbst gehosteten Umgebungen. - Sehr gute Kenntnisse in Kubernetes, Docker und Linux. - Erfahrung mit CI/CD-Pipelines, Cloud-Plattformen (insbesondere Azure) sowie PostgreSQL. - Praktische Erfahrung mit LLM-Gateways, RAG-Architekturen, Vector-Datenbanken und Modell-Serving-Lösungen. - Solide Python-Kenntnisse für Automatisierung und Integrationen. - Eigenständige und strukturierte Arbeitsweise mit hoher Eigenverantwortung sowie Sicherheits- und Datenschutzbewusstsein. - Ausgeprägtes Architektur- und Platformverständnis. Benefits - Offene und kooperative Unternehmenskultur sowie eine vertrauensvolle Arbeitsatmosphäre. - Umfassende Einarbeitung mit Unterstützung des gesamten AIS Teams. - Flache Hierarchien – kurze Entscheidungswege und hohe Gestaltungsfreiheit. - Strategische Gestaltungsrolle mit großem Einfluss auf die zukünftige Plattformlandschaft. - Mitarbeit an einem der spannendsten Technologiefelder der IT: souveränes LLM-Hosting und KI-Infrastrukturen. - Moderne Infrastruktur mit Kubernetes, Docker, CI/CD und Cloud-Technologien. - Möglichkeit, Standards, Prozesse und Architekturentscheidungen aktiv mitzugestalten. - Individuelles Weiterbildungsbudget für Konferenzen, Zertifizierungen und Fachtrainings. - Klare Karriere- und Entwicklungspfade. - Möglichkeit zur Spezialisierung als AI Platform Engineer bzw. LLMOps-Experte. - Kleines, fokussiertes und agiles Team mit kurzen Entscheidungswegen. - Offene Feedback-Kultur mit regelmäßigen 1:1-Gesprächen und Retrospektiven.

Role Description Design, build, and operate a sovereign AI toolchain used in isolated or tightly controlled environments, including model serving, retrieval, orchestration, observability, and secure platform operations for enterprise AI engineering workloads. This role centers on open-source or open-weight LLM stacks, air-gapped or isolated deployment models, Kubernetes-based platform engineering, GPU-enabled environments, and auditable AI operations suitable for sovereignty-sensitive programs. Key responsibilities - Design and run Kubernetes environments optimized for AI inference, retrieval, experimentation, and agent execution in secure or isolated settings. - Deploy and operate open-source or open-weight model stacks, model gateways, vector databases, and supporting platform components. - Build reproducible platform automation using Infrastructure as Code and GitOps approaches for stable, auditable delivery. - Manage local registries, package mirrors, secrets, access controls, storage, networking, and observability in environments with limited or no public cloud dependency. - Optimize GPU, compute, and storage usage for reliable AI workloads while maintaining security and data sovereignty requirements. Examples of market tools, models, and platform components expected: - Inference and local serving stacks such as vLLM, Ollama, llama.cpp, or OpenAI-compatible self-hosted endpoints. - Open-source or open-weight models appropriate for sovereign deployment, for example coding-capable and general-purpose families hosted internally through approved serving layers. - Platform tooling such as Kubernetes, Helm, Terraform, Ansible, ArgoCD, private registries, Qdrant or similar vector stores, and Open WebUI or comparable internal interfaces. - Developer-facing integration options such as VS Code-compatible extensions, Continue-style local model connectors, or editor integrations pointed at internal APIs instead of external SaaS endpoints. - Hardware awareness covering GPU-backed nodes, CPU-only fallback options, storage performance, network isolation, and on-prem or dedicated infrastructure patterns. Qualifications - 5+ years in platform engineering, DevOps, SRE, or MLOps, with strong Kubernetes and Linux expertise. - Proven experience with AI infrastructure, model serving, private or on-prem deployments, and production operations for LLM-based workloads. - Strong hands-on skills in Python plus automation tooling such as Terraform, Ansible, Helm, and GitOps workflows. - Good understanding of networking, storage, access control, monitoring, and operational hardening in high-security environments. - Comfortable working in sovereignty-driven environments where auditability, isolation, and controlled data handling are mandatory. Additional Information - You will be working in the European Union to meet our customers' data security and privacy requirements. - Please be informed that our remote working possibility is only available within Hungary due to European taxation regulation. Company Description As Hungary’s most attractive employer in 2025 (according to Randstad’s representative survey), Deutsche Telekom IT Solutions is a subsidiary of the Deutsche Telekom Group. The company provides a wide portfolio of IT and telecommunications services with more than 5300 employees. We have hundreds of large customers, corporations in Germany and in other European countries. DT-ITS received the Best in Educational Cooperation award from HIPA in 2019, acknowledged as the Most Ethical Multinational Company in 2019. The company continuously develops its four sites in Budapest, Debrecen, Pécs and Szeged and is looking for skilled IT professionals to join its team.