DevOps / MLOps Engineer - Assistant Vice President

Job Description:

Job Title DevOps / MLOps Engineer

Corporate Title Assistant Vice President

Location Cary, NC

Who we are:

In short – an essential part of Deutsche Bank’s technology solution, developing applications for key business areas.

Our Technologists drive Cloud, Cyber and business technology strategy while transforming it within a robust, hands-on engineering culture. Learning is a key element of our people strategy, and we have a variety of options for you to develop professionally. Our approach to the future of work champions flexibility and is rooted in the understanding that there have been dramatic shifts in the ways we work.

Having first established a presence in the Americas in the 19th century, Deutsche Bank opened its US technology center in Cary, North Carolina in 2009. Learn more about us here.

Overview

We are seeking a skilled DevOps/MLOps Engineer with deep expertise in Google Cloud Platform (GCP) to help us build a world-class machine learning and AI capabilities within the bank. You will be instrumental in designing, implementing, and maintaining scalable infrastructure and automated pipelines that support the full machine learning lifecycle—from experimentation to deployment and monitoring. This role involves close collaboration with data scientists, data engineers, product managers, and platform teams to operationalize models, streamline workflows, and uphold the highest standards of security, privacy, and compliance. You’ll help define and evolve our MLOps practices, ensuring our AI solutions are reliable, reproducible, and impactful.

What We Offer You

• A diverse and inclusive environment that embraces change, innovation, and collaboration

• A hybrid working model with up to 60% work from home, allowing for in-office / work from home flexibility, generous vacation, personal and volunteer days

• A commitment to Corporate Social Responsibility

• Employee Resource Groups support an inclusive workplace for everyone and promote community engagement

• Access to a strong network of Communities of Practice connecting you to colleagues with shared interests and values

• Competitive compensation packages including health and wellbeing benefits, retirement savings plans, parental leave, and family building benefits

• Educational resources, matching gift, and volunteer programs

What You’ll Do

• Build and maintain CI/CD pipelines for ML workflows using GCP-native tools such as Cloud Build, Artifact Registry, and Cloud Deploy

• Containerize and orchestrate ML workloads using Docker, Kubernetes, and GKE (Google Kubernetes Engine)

• Collaborate with cross-functional teams to transition models from development to production, integrating them into customer-facing applications.

• Implement robust model monitoring, logging, and alerting using tools like Vertex AI Model Monitoring, Cloud Logging, and Cloud Monitoring

• Define and enforce best practices for model versioning, testing, and reproducibility using tools like MLflow and Vertex AI Pipelines

• Ensure infrastructure adheres to security and compliance standards, working closely with Cybersecurity and Data Governance teams

Skills You’ll Need

• Bachelor's degree or equivalent is required

• Experience in MLOps or DevOps roles, with a strong focus on cloud-native ML infrastructure

• Proven experience deploying ML models in production (batch and real-time), ideally in regulated or privacy-sensitive environments.

• Proficiency in Python, with solid software engineering fundamentals and experience using Terraform or Deployment Manager for infrastructure-as-code

• Hands-on experience with GCP ML tools: Vertex AI, AI Platform, BigQuery ML and CI/CD: Cloud Build, GitHub Actions, Jenkins

• Containerization & Orchestration: Docker, Kubernetes, GKE

Skills That Will Help You Excel

• Experience deploying and managing generative AI models (LLMs) in production, including prompt engineering, evaluation pipelines, and safety guardrails

• Familiarity with observability tools such as MLflow, LangFuse, or Braintrust

• Exposure to data governance and privacy frameworks in cloud environments

Expectations

It is the Bank’s expecta