{"id":706474,"url":"https://alion.io/job/inovex-gmbh-cloud-engineer-data-ai","title":"Cloud Engineer* Data & AI","company":{"id":15851,"name":"inovex","domain":"inovex.de","url":"https://alion.io/company/inovex-gmbh","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Recruitee","truth_index":{"grade":"D","score":52,"open_postings":20,"ghost_share":0.8,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-17T05:46:00Z"}},"role":"DevOps","role_family":"DevOps","seniority":null,"employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Karlsruhe, Germany"],"countries":["DE"],"hiring_countries":["DE"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":59000,"max_usd":117000,"period":"year","method":"role_country_seniority_unknown","sample_n":164},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon S3","optional":false},{"name":"Apache Kafka","optional":false},{"name":"ArgoCD","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Cilium","optional":false},{"name":"Databricks","optional":false},{"name":"dbt","optional":false},{"name":"GCP","optional":false},{"name":"GitOps","optional":false},{"name":"Grafana","optional":false},{"name":"Helm","optional":false},{"name":"KServe","optional":false},{"name":"Kubernetes","optional":false},{"name":"Kyverno","optional":false},{"name":"MLFlow","optional":false},{"name":"OpenTelemetry","optional":false},{"name":"pgvector","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Prometheus","optional":false},{"name":"Python","optional":false},{"name":"Ray","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"Terraform","optional":false},{"name":"vLLM","optional":false}],"status":"live","first_seen_at":"2021-03-04T15:47:59Z","employer_posted_date":"2021-03-04","last_verified_at":"2026-10-18T00:07:37Z","board_verified":true,"closed_at":null,"days_open":2053,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":2052},"description":"Was du bei uns bewegen kannst\nAls Cloud Engineer liegt dein Schwerpunkt auf der Implementierung moderner Data- und AI-Infrastrukturen, wobei du GPU-Cluster orchestrierst, Datenplattformen strukturierst und Pipelines für ein effizientes Modell-Training sowie den stabilen Betrieb von Inferenz-Schnittstellen automatisierst.\n\nDatenplattformen konzipierst du, von der Storage-Architektur über Lakehouse-Formate bis zur Integration von Orchestrierung und Streaming-Komponenten.\n\nTools wie Airflow, Spark on Kubernetes oder Ray setzt du auf, integrierst sie miteinander und stellst sicher, dass Data- und ML-Workflows zuverlässig in Produktion laufen.\n\nInfrastructure-as-Code und GitOps sind für dich der Standard. Bei sensiblen Datenprodukten baust du Sicherheit von Beginn an ein, von Network Policies bis zu den Anforderungen aus der Data Governance.\n\nMonitoring, Incident-Handling und GPU-Kapazitätsplanung liegen in deiner Verantwortung.\n\nIn unseren Projekten verwenden wir häufig folgende Technologien:\nAWS, Azure, Google Cloud, StackIT, Kubernetes\n\nTerraform, ArgoCD, Helm, Cilium, Kyverno\n\nAirflow, Spark, Kafka, Ray, Kueue\n\nDatabricks, Snowflake, dbt, Iceberg\n\nS3, PostgreSQL, pgvector, MLflow, vLLM, KServe\n\nPrometheus, Grafana, OpenTelemetry\n\nPython, Go\n\nIntern wie extern kannst du dich bei uns auf vielfältige Art einbringen: Deinen anfangs gewählten technologischen Schwerpunkt kannst du jederzeit verlagern. Als Expert:in im Bereich Engineering hast du außerdem die Möglichkeit, jüngere Kolleg:innen durch Mentoring zu unterstützen.\nRequirements\nWer gut zu uns passen würde\nOb du ein Studium oder eine Ausbildung im IT-Bereich abgeschlossen hast, ist für uns nebensächlich. Für uns zählen deine fachlichen Skills und deine Persönlichkeit:\nDu hast fundierte Kubernetes-Erfahrung im produktiven Betrieb und bringst tiefgehende Kenntnisse im Umgang mit einem der großen Cloud-Provider (AWS, Azure, Google Cloud, StackIT) mit.\n\nInfrastructure-as-Code setzt du routiniert ein. 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