DevOps Automation Engineer - Remote Danaher · Remote · US · DevOps & Release –ago

Bring more to life.

At Danaher, our work saves lives. And each of us plays a part. Fueled by our culture of continuous improvement, we turn ideas into impact – innovating at the speed of life.

Our 60,000+ associates work across the globe at more than 15 unique businesses within life sciences, diagnostics, and biotechnology.

Are you ready to accelerate your potential and make a real difference? At Danaher, you can build an incredible career at a leading science and technology company, where we’re committed to hiring and developing from within. You’ll thrive in a culture of belonging where you and your unique viewpoint matter.

Learn about the Danaher Business System which makes everything possible.

The Staff Dev Ops Engineer owns the delivery and operational backbone of the platform behind our AI initiatives — CI/CD,infrastructure as code, environment management, observability, and production operations. You will work directly with the teams building AI into consequential work across the company: molecular design, autonomous labs, supply chain, professional services, and more. You will set the technical patterns others build on and help define what delivery infrastructure looks like as workloads become increasingly LLM-driven and agentic.

This position reports to the Senior Director, Data and AI Platform and is part of the Chief Information Officer (CIO) Officelocatedin Washington, DC and will be fully remote.

In this role, you will have the opportunity to:

• Design, build, automate, and operate secure, scalable cloud infrastructure across Azure using Infrastructure as Code (Terraform, Pulumi, etc.), while embedding governance, compliance, security, data quality, and auditability by design.
• Develop and maintain the platform engineering ecosystem, including CI/CD pipelines, self-service capabilities, and resource provisioning frameworks that enable data scientists and engineers to rapidly and safely access compute, data, and ML resources without deep infrastructure expertise.
• Establish and manage platform operations, including observability, monitoring, alerting, reliability practices, support models, and operational processes that ensure platform stability, performance, and maintainability.
• Evaluate, integrate, and optimize emerging technologies and services, providing practical recommendations and implementing modern tooling that enhances platform capabilities, scalability, and user experience.
• Collaborate across platform leadership, engineering teams, and internal customers to translate requirements into well‑engineered solutions, while mentoring junior engineers, contributing to technical standards and documentation, and fostering a culture of technical excellence, continuous learning, and collaboration.

The essential requirements of the job include:

• 5+ years of software, platform, or infrastructure engineering experience, including hands‑on data and/or AI/ML infrastructure work; CS/Engineering degree or equivalent practical experience.

• Deep, hands‑onexpertisewith at least one major cloud platform (AWSorAzure), plus working familiarity with multi-cloud environments and their data and AI services.

• Strong experience with Infrastructure as Code (e.g., Terraform/ Pulumi), CI/CD tooling (e.g., Git Hub Actions, Git Lab CI,etc), and containerization/orchestration (Docker, Kubernetes), withproficiencyin at least one language (Python, Go, Bash) for automation and tooling.

• Solid security and networking fundamentals for provisioning secure cloud resources, and atrack record operating production systems: monitoring, observability, incident response, and reliability practices.

• Proven ability to set technical direction at platform scale: driving cross-team architecture and design decisions,establishing standards,…