DevOps Engineer Submission Data and Content Generation & Reuse

About the Role

The Senior DevOps & Cloud Engineer will take ownership and drive strategic technical initiatives, focusing on optimizing and automating the deployment and management of platform and cloud-based services. This role involves leading the cloud architecture and MLOps/DevOps foundation for next-generation Agentic AI platforms, bridging the gap between AI development and production-grade software. The engineer will build secure, scalable, and compliant infrastructure that automates complex regulatory workflows across Pharma R&D, challenge the status quo, foster collaboration, and mentor junior team members while ensuring cost-effectiveness, scalability, and security across the digital product lifecycle.

Description of the Area

The Clinical Submission Data and Content Generation & Reuse function modernizes the creation and management of clinical data and regulatory submission assets. It develops and deploys platforms for structured content management, enabling the reuse of approved components across documents. This group also pioneers the use of agentic AI to assist in generating, reviewing, and assembling complex submission assets, aiming to improve quality and reduce authoring timelines.

Key Responsibilities

• Architect and deploy scalable infrastructure from scratch for greenfield AI-driven clinical authoring products with minimal initial guidance.
• Optimize and automate cloud and platform services, manage infrastructure using IaC principles, and implement robust security and monitoring practices.
• Establish end-to-end observability (tracing, metrics, logging) to reduce mean-time-to-resolution (MTTR) for critical submission pipelines.
• Identify process gaps at the company level and bring in outside best practices to improve current methodologies.
• Prioritize and communicate effectively with stakeholders, maintaining a "bigger picture" view to understand how technical components fit into the overall product strategy and organizational goals.
• Act as a technical mentor to junior engineers and actively share knowledge in internal and external events.
• Align personal and team development plans with the global strategy and participate in initiatives reaching outside the regular project scope.
• Operate at the Product or Site level, managing complex infrastructures, CI/CD pipelines, and scripts for large workloads and products in Production environments.
• Formulate and implement technical strategies aligned with organizational objectives, investing time in initiatives that boost creativity and innovation while maintaining the highest engineering quality.

Requirements & Tech Stack

• Core Stack: AWS, Kubernetes, Terraform, Python, GitHub Actions/GitLab CI, Grafana/ELK
• Preferred: Multi-cloud routing, Jaeger/tracing, Rust/JS

Qualifications

• Demonstrated experience in Production environments managing large workloads and products across traditional and cloud application architectures (Serverless, Kubernetes, Cloud DB Services).
• Proven track record of mentoring junior engineers, fostering good collaboration, and skillfully navigating group dynamics.
• Experience identifying gaps in Agile and DevOps principles at the company level and successfully implementing external best practices.
• Advanced knowledge of at least one programming language (Python, JavaScript) and advanced terminal skills (Bash/PowerShell scripting, networking tools, process monitoring).
• High proficiency in Infrastructure as Code (Terraform, CDK, CloudFormation), advanced Docker containerization, and Version Control (Git) with the ability to troubleshoot complex issues and implement best practices.
• Expertise in CI/CD platforms (Gitlab CI, Jenkins, or Github Actions) and advanced monitoring, logging, metrics, and tracing tools (Elastic Stack, Grafana).
• Hands-on experience with Docker and Kubernetes.
• Strong understanding of cloud networking concepts including VPC/VNet, subnets, routing, DNS, firewalls/security groups, load balancers, and private connectivity.
• Familiarity with GxP compliance, CSV (Computer Systems Validation), or automated compliance testing within CI/CD pipelines.
• Experience supporting data/ML workloads (e.g., orchestrating vector databases, managing GPU-backed Kubernetes nodes, or deploying MLOps/LLMOps pipelines).
• Strong communication and stakeholder management skills, with the ability to adjust communication styles based on the audience.
• Proactive mindset dedicated to continuous improvement, identifying technical opportunities, and independently leading complex troubleshooting efforts across multiple teams.

Shift: CET time zone