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.

In this role, you will have the opportunity to: 

• Engineer security controls for the LLM/AI stack: model access controls, prompt handling, RAG pipelines, tool/agent permissions, output filtering, logging, guardrails, and AI DLP. 

• Build automation (Python, SOAR) for detection, triage, remediation, and control evidence — with human oversight, test harnesses, and rollback. 

• Contribute to AI-security reference patterns; evaluate model/data supply-chain risk. 

• Support the sustainability model: automation runbooks, auditability, and control-evidence pipelines. 

The essential requirements of the job include: 

• Bachelor's degree in Cybersecurity, Computer Science, Software/AI Engineering, or related field. 

• 8+ years in security engineering, application/cloud security, or DevSecOps, including experience building or securing AI/ML or LLM-based systems. 

• Hands-on experience securing the LLM/AI application stack: prompt handling, RAG pipelines, tool/agent permissions, output filtering, guardrails, or AI DLP. 

• Proficiency in Python for building security automation and integrations (including SIEM/SOAR). 

• Working knowledge of AI-security frameworks such as OWASP LLM Top 10, NIST AI RMF, MITRE ATLAS, or EU AI Act technical requirements. 

It would be a plus if you also possess previous experience in: 

• Experience red-teaming or evaluating LLM/agentic-AI applications (e.g., promptfoo, garak, PyRIT). 

• GIAC GMLE / GIAC AI-ML Security, or a cloud AI/security certification (Microsoft, AWS, or GCP). 

• Experience with MLOps/CI-CD security integration.