Staff DevOps Automation Engineer - USA Remote

Danaher is a science and technology company focused on life sciences, diagnostics, and biotechnology. The Staff DevOps Automation Engineer will own the delivery and operational backbone of AI platforms, including cloud infrastructure, infrastructure as code, CI/CD, environment management, observability, and production operations. The role will establish technical patterns, collaborate across engineering teams, and mentor junior engineers while enabling secure and scalable data and AI workloads.

Responsibilities:

• 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
• Ability to travel – up to 10%

Requirements:

• • 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-on expertise with at least one major cloud platform (AWS or Azure), 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., GitHub Actions, GitLab CI, etc), and containerization/orchestration (Docker, Kubernetes), with proficiency in at least one language (Python, Go, Bash) for automation and tooling
• • Solid security and networking fundamentals for provisioning secure cloud resources, and a track 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, and mentoring engineers in ambiguous, high-impact problem spaces
• • Ability to travel – up to 10%
• • Life sciences, diagnostics, or biotechnology (e.g., partnering with R&D, quality, clinical, manufacturing, or commercial teams)
• • Data and engineering practices in industries governed by regulatory standards (e.g., HIPAA, GxP), compliance frameworks (e.g., SOX), and rigorous data governance requirements
• • Working in a matrixed environment