{"id":3007707,"url":"https://alion.io/job/kfw-cloud-engineer-ai-workplace-wmd","title":"Cloud Engineer AI Workplace (w/m/d)","company":{"id":184845,"name":"KfW","domain":"kfw.de","url":"https://alion.io/company/kfw-stories","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"BeeSite","truth_index":{"grade":"B","score":75,"open_postings":22,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":31,"computed_at":"2026-10-21T05:46:15Z"}},"role":"DevOps","role_family":"DevOps","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Berlin, Germany"],"countries":["DE"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":55000,"max_usd":109000,"period":"year","method":"role_country_seniority_unknown","sample_n":171},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Azure","optional":false},{"name":"Azure DevOps","optional":false},{"name":"CI/CD","optional":false},{"name":"GitHub","optional":false},{"name":"Machine Learning","optional":false},{"name":"Microsoft Entra ID","optional":false},{"name":"Terraform","optional":false}],"status":"live","first_seen_at":"2026-10-21T14:23:01Z","employer_posted_date":"2026-10-21","last_verified_at":"2026-10-21T23:30:18Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Das erwartet Sie\nDie KfW nutzt Cloud-Technologien, um Anwendungen mit Künstlicher Intelligenz umzusetzen. Die Vision unseres interdisziplinären Teams ist es, durch neue Technologien und innovative Methoden im Kontext von KI und Data Science den Weg der KfW zu einer digitalen Förderbank zu ebnen.\n Unser IT-Team gestaltet und etabliert die skalierbare sowie regulatorisch konforme Nutzung. Azure Machine Learning dient dabei als zentraler Data-Science-Arbeitsplatz für die Entwicklung, Erprobung von KI-Lösungen innerhalb der KfW.\n Die Aufgabengebiete auf einen Blick:\n Technische Weiterentwicklung des bestehenden Data-Science-Arbeitsplatz auf Basis von Azure Platform as a Service (Azure ML)\n Integration und Betrieb relevanter Azure-Dienste, beispielsweise Azure Machine Learning, Azure Storage, Azure Key Vault, Azure Container Registry, Netzwerkkomponenten und Monitoring\n Evaluierung, Validierung und Integration neuester Funktionen von Azure ML in die Plattform, beispielsweise für Agentic AI, MLOps-Workflows\n Analyse und Behebung technischer Störungen sowie kontinuierliche Optimierung von Stabilität, Kosten, Performance und Automatisierungsgrad\n Umsetzung von Sicherheits-, Compliance- und Governance-Vorgaben in Zusammenarbeit mit den zuständigen Teams\n Innovationsarbeit in der KfW: Digitalisierung als Treiber für Veränderung verstehen und gemeinsam mit der KfW aktiv voranbringen \n Das bringen Sie mit\n Abgeschlossenes IT-Studium oder vergleichbare Qualifikation\n Erfahrung im Betrieb und in der Weiterentwicklung von Cloud-Plattformen auf Microsoft Azure\n Sehr gute Kenntnisse in Infrastructure as Code, insbesondere Terraform\n Praktische Erfahrung mit CI/CD und Versionsverwaltung, beispielsweise Azure DevOps oder GitHub\n Kenntnisse in Azure-Netzwerk-, Identitäts- und Sicherheitskonzepten, beispielsweise Microsoft Entra ID, Private Endpoints, Managed Identities und Key Vault\n Idealerweise Erfahrung mit Azure Machine Learning, MLOps, Container-Technologien\n Strukturierte, lösungsorientierte Arbeitsweise sowie Freude an der Zusammenarbeit in interdisziplinären Teams Lust, etwas zu verändern und zu gestalten\n Fließendes Deutsch und gutes Englisch\n Stark ausgeprägte analytische und konzeptionelle Fähigkeiten, Zielorientierung sowie sehr gute 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