• Design, implement, and maintain deployment pipelines for both Cloud and Edge components • Develop Infrastructure as Code using Terraform with focus on modularity and Remote State management • Build and maintain advanced CI/CD pipelines exclusively using GitHub Actions • Manage AWS IoT Greengrass deployments on Linux edge devices for distributed computing • Configure and maintain KEPServerEX on Windows systems for OPC UA industrial connectivity • Ensure secure connectivity between Factory environments and Cloud infrastructure using VPN and Direct Connect • Implement end-to-end observability solutions using CloudWatch and infrastructure metric collection • Manage AWS IoT SiteWise for collecting, organizing, and analyzing industrial equipment data • Design and maintain streaming data pipelines using AWS Kinesis or MSK for real-time data processing • Automate Edge device lifecycle management including provisioning, updates, and monitoring • Implement security best practices for hybrid Cloud-Factory architectures • Monitor and optimize infrastructure performance, cost, and reliability • Troubleshoot complex issues across Cloud and Edge environments • Document infrastructure architecture, deployment processes, and operational procedures • Collaborate with development teams to enable efficient deployment workflows • Stay current with AWS IoT services, edge computing technologies, and DevOps best practices.

Role Description Als „DevOps/Platform Engineer (m/w/d)“ stellst du für unseren KI-Plattform Alan eine sichere, skalierbare, beobachtbare Plattform bereit und etablierst das Prinzip „You build it, you run it“ im Team. Du unterstützt die produktiven Teams auf „paved paths“ (Self-Service, Guardrails) und sorgst für vorhersehbare Performance und Kosten. - Ownership für zentrale Plattform-/Serving-Komponenten übernehmen - K8s-Cluster, Networking (Ingress), Storage (Datenbanken, Snapshots) und OS/Kernel-Patching betreiben und deren sicheren und stabilen Betrieb sicherstellen - Multi-Cloud-Ressourcen (insb. Open Telekom Cloud) per Konsole und IaC (Terraform) modellieren - CI/CD-Pipelines und Release-/Versionierungs-/Rollback-Strategien aufbauen - OpenTelemetry-basiertes Tracing, Metrics und Logs im Bereich Observability & Site Reliability Engineering implementieren, SLIs/SLOs, Alerting und Error Budgets definieren - Plattform für Model Serving gemeinsam mit unseren AI Engineers bereitstellen: GPU-Scheduling, Autoscaling, Inference-Gateways, Observability (Latency/QPS/Token-Kosten) Qualifications - Masterstudium oder Promotion in einem der MINT-Fächer oder einem geisteswissenschaftlichen Fach mit MINT-Vertiefung erfolgreich abgeschlossen - Mindestens 2 Jahre relevante Berufserfahrung in den Bereichen DevOps, Site Reliability Engineering oder Platform Engineering - Nachweisliche Verantwortung für Kubernetes, IaC, CI/CD, Observability sowie den produktiven Betrieb – idealerweise im SaaS-Umfeld - Praxis-Know-how in Git-basierten Deployments, modularer IaC, Secret-/Config-Management sowie Incident-Erfahrung - Security-Fachwissen in Netzwerksicherheit, Secrets, Härtung (CIS), Software-Supply-Chain und Zugriffsprinzipien (Least Privilege) - Idealerweise erste Praxiserfahrung im Betrieb von Inferenz-Workloads (vLLM o. ä.), GPU-Capacity-Management, Autoscaling und Observability - Neugier und Wissbegierde sowie ausgeprägte Problemlösungs- und Kommunikationsfähigkeit - Überzeugende und effiziente Kommunikation in deutscher und englischer Sprache Benefits - Arbeiten an einer hochmodernen, skalierbaren AI-Plattform mit viel Gestaltungsspielraum - Früh Verantwortung für zentrale Infrastruktur- und Architekturentscheidungen übernehmen - Fachlicher Austausch auf Augenhöhe mit zukünftigen Kolleg:innen - Budget und Zeit für eigene Innovationsprojekte - Fachliche und persönliche Weiterentwicklung durch speziell abgestimmte Weiterbildungen, Zertifizierungen und Laufbahnprogramme - Schwerpunktsetzung und Ausbau in Spezialgebieten - Attraktives Fixgehalt zzgl. Umsatz- und Ergebnisbeteiligung - Überstunden ausgleichen und Reisezeiten als Arbeitszeit buchen - Freie Wahl des Arbeitsorts und flexible Arbeitszeit - Top ausgestatteter Arbeitsplatz, JobRad, Body & Mind Workout, GamesNights, Grillen auf der Dachterrasse - Team-Aktionen mit unternehmungslustigen Kolleg:innen, Sommerfeste mit Familienmitgliedern und viele weitere Benefits

CAPCO POLAND *We are looking for Poland based candidate. Hybrid work. Warsaw is preferred. At Capco Poland, we’re not just another consultancy - we’re the spark behind digital transformation in the financial world. As a global leader in technology and management consulting, we thrive on helping clients tackle the toughest challenges across banking, payments, capital markets, wealth, and asset management. Our secret? A culture that’s fast, flexible, and fiercely entrepreneurial. We move quickly, think creatively, and always put our people first. We’re passionate about growth - both for our clients and ourselves - and that means attracting the very best talent to join us on this exciting journey. We’re proud to be: • Trailblazers in banking, payments, capital markets, wealth, and asset management • Champions of an agile, nimble, and innovative work environment • Dedicated to building a team of top-notch professionals who share our drive and vision THINGS YOU WILL DO Platform Engineering for ML - Design, build, and improve MLOps platform components that support the full model lifecycle (development à validation à deployment à monitoring). - Create reusable templates and standardized pipelines to reduce time-to-production and improve consistency across teams. Model deployment & release engineering - Implement robust deployment patterns for credit risk models (primarily batch; other patterns as required). - Build & maintain CI/CD pipelines using Jenkins and GitHub, with appropriate quality gates and traceability. - Automate environment configuration and repeatability using Ansible. Monitoring, observability & operational readiness - Implement model and pipeline monitoring covering operational health, data quality signals, and model performance/drift indicators. - Establish dashboards, alerting, and runbooks; partner with stakeholders to ensure alerts are actionable and aligned to business impact. - Drive continuous improvement through post-release reviews and reliability enhancements (no on-call requirement). Collaboration & stakeholder management - Work closely with credit risk modellers to productionise models built with tools such as TensorFlow, MLFlow, and similar. - Translate modelling needs into scalable engineering solutions, balancing pace with control expectations. - Mentor junior team members (nice-to-have) and contribute to shared engineering standards and documentation. SKILLS & EXPERIENCES YOU NEED TO GET THE JOB DONE - 5+ years’ experience across MLOps/DevOps/Platform Engineering, with a track record of delivering production-grade ML or data solutions. - Strong experience building CI/CD and automation using Jenkins and GitHub. - Strong experience with Airflow (Bash), Bash itself, and Groovy for pipeline automation. - Hands-on configuration automation using Ansible. - Strong coding/scripting capability in Python (including PySpark), plus working knowledge of Spark. - Experience with ML tooling such as MLFlow, TensorFlow, and similar, including model packaging and deployment considerations. - Proven ability to implement observability (metrics/logs/dashboards/alerting), with tooling flexibility (e.g., Grafana, Splunk, or similar). - Comfortable working in hybrid environments; experience with Hadoop and an ability to integrate with cloud services (preference for GCP). Nice to have: - Exposure to GCP services, especially Vertex AI and BigQuery. - Experience with secrets management (tooling flexible). - Familiarity with Model Risk Management, SDLC controls, and data lineage concepts in regulated environments. - Prior experience mentoring junior engineers and helping teams adopt standard patterns. ONLINE RECRUITMENT PROCESS STEPS - Screening call with the Recruiter - Capco Hiring Manager Interview - Client’s interview - Feedback/Offer We offer a flexible collaboration model based on a B2B contract, with the opportunity to work on diverse projects.

• Supporting developers through internal productivity platforms and responding to internal customer requests, leveraging team collaboration and AI tools where appropriate • Owning and maintaining developer productivity services such as GitHub, Jenkins, and Artifactory, ensuring reliability and scalability • Creating and managing Kubernetes operators, while troubleshooting infrastructure (network)‑related issues (it's always DNS ^^) • Automating recurring tasks for teams and developers using an AI‑first engineering approach, including building integrations with third‑party systems and APIs • Participating in the on‑call rotation for critical services, maintaining internal technical documentation, and continuously learning and experimenting to improve how software is built