Deutsche Bank

Cloud Engineer

Bucharest, Romania
GCP Cloud Build Terraform GitHub Actions Vertex AI BigQuery ML Cloud Functions MLflow Kubeflow Cloud Monitoring Cloud Logging Error Reporting Python Java Docker Kubernetes GKE
Description

Cloud Engineer (f/m/x)

Location: Bucharest Ion Mihalache Blvd

Time Type: Full time

Job Description

Job Description:

DB Global Technology is Deutsche Bank’s technology center in Central and Eastern Europe. Since its set-up in 2013, Bucharest Technology Centre (BEX) has constantly proven its capacity to deliver global technology products and services, playing a dynamic role in the Bank’s technology transformation.

We have a robust, hands-on engineering culture dedicated to continuous learning, knowledge-sharing, technical skill development and networking. We are an essential part of the Bank’s technology platform and develop applications for many important business areas.

Corporate Banking is a technology centric business, with an increasing move to real-time processing, an increasing appetite from customers for integrated systems and access to supporting data. This means that technology is more important than ever for the business.  

Deutsche Bank is one of the few banks with the scale and network to compete aggressively in this space, and the breadth of investment in this area is unmatched by our peers. Joining the team is a unique opportunity to help rebuild the core of some of our most mission critical processing systems from the ground-up. 

Our Corporate Bank Technology team is a global team of 3000 coders (and growing!) across 30 countries. The primary businesses that Corporate Bank support are Cash Management, Securities Services, Trade Finance and Trust & Agency Services.  CB Technology support these businesses through CIO aligned teams and also by 'horizontals' such as Client Connectivity, Surveillance and Regulatory, Infrastructure, Architecture, Production, and Risk & Control.

We are seeking an experienced and motivated Data Science Engineer to join our AI Tribe. In this role, you will design and implement cutting-edge data science solutions that address complex business challenges and contribute directly to development and delivery objectives. The ideal candidate brings a solid foundation in both data engineering and data science, a strong grasp of modern methodologies and technologies, and a proven ability to deliver impactful, production-grade solutions in a business environment.

Responsibilities

• Independently design and implement cloud-native infrastructure on GCP, including networking, compute, storage, and IAM configurations.

• Build and manage automated deployment pipelines using tools like Cloud Build, Terraform, and GitHub Actions to support infrastructure-as-code and continuous delivery.

• Support AI/ML workloads by provisioning and managing services such as Vertex AI, BigQuery ML, and Cloud Functions, enabling scalable model training, deployment, and monitoring.

• Collaborate with MLOps and data science teams to integrate ML lifecycle automation, including model versioning, CI/CD for ML, and performance monitoring. • Implement and maintain security and compliance controls, including encryption, access management, and audit logging.

• Monitor and troubleshoot cloud infrastructure using GCP-native tools like Cloud Monitoring, Cloud Logging, and Error Reporting to ensure high availability and resiliency.

• Stay current with emerging GCP technologies and best practices, and proactively recommend improvements to architecture and operational processes.

• Document cloud architecture, operational procedures, and governance standards to support transparency and knowledge sharing.

Skills

• Solid experience in cloud engineering, DevOps, or infrastructure operations, with a strong focus on Google Cloud Platform.

• Proficiency in Python or Java, with experience in scripting and automation. • Hands-on experience with infrastructure-as-code tools such as Terraform or Deployment Manager.

• Familiarity with cloud networking, IAM, security best practices, and cost management on GCP.

• Experience with CI/CD pipelines, containerization (Docker), and orchestration (Kubernetes or GKE).

• Exposure to AI/ML tooling such as Vertex AI, MLflow, or Kubeflow, and understanding of MLOps principles including model deployment, monitoring, and governance.

• Strong analytical and problem-solving skills.

• Ability to work independently and take ownership of deliverables.

• Excellent communication and collaboration abilities.

• Bachelor’s degree or equivalent in Computer Science, Engineering, or a related field.

Well-being & Benefits

Emotionally and mentally balanced:

  • Empowering managers who value your ideas and decisions. Show your positive attitude, determination, and open-mindedness.

  • A professional, passionate, and fun workplace with flexible Work from Home options.

  • A modern office with fun and relaxing areas to boost creativity.

  • Continuous learning culture with coaching and support from team experts.

Physically thriving:

  • Private healthcare and life insurance with premium benefits for you and discounts for your loved ones.

Socially connected:

  • Enjoy retailer discounts, cultural and CSR activities, employee sport clubs, workshops, and more.

Financially secure:

  • Competitive income, performance-based promotions, and a sense of purpose.

  • 24 days holiday, loyalty days, and bank holidays (including weekdays for weekend bank holidays).

We strive for a culture in which we are empowered to excel together every day. This includes acting responsibly, thinking commercially, taking initiative and working collaboratively.

Together we share and celebrate the successes of our people. Together we are Deutsche Bank Group.

We welcome applications from all people and promote a positive, fair and inclusive work environment.

Deutsche Bank
Deutsche Bank

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