Senior AI Compliance, Risk & Security Engineer

Overview

In this role you will help Danaher build, scale and operate trusted AI solutions across operating companies. You will work with governance, data, product, and engineering teams to ensure AI systems are compliant, transparent and scalable. Your efforts will focus on mitigating risk, guiding responsible AI practices, and enabling enterprise-wide adoption. This is a hands-on, cross-functional opportunity to shape how AI delivers measurable business impact at a global science and technology leader.

Responsibilities

• Assess and advance AI/ML/DS solutions, architectures, models and data flows, identifying compliance, privacy, cybersecurity and operational risks before production
• Collaborate with Governance, Enterprise Data, Product Owners, Architects, AI Scientists and Engineers to enable trusted adoption and scalable AI solutions
• Develop guardrails, risk-assessment methods, compliance evidence and controls to balance innovation with security and policy requirements
• Evaluate data sourcing, processing and governance within AI solutions to ensure transparency, traceability and risk mitigation
• Guide the team in mitigating model bias, explainability, robustness, privacy and regulatory compliance to scale solutions across Danaher

Key requirements

• Strong understanding of AI, machine learning, generative AI and modern AI architectures with hands-on experience delivering or supporting AI/data solutions
• Experience assessing technology, data, privacy, compliance, cybersecurity or operational risks in AI/software/analytics
• Ability to translate regulatory and governance requirements into practical controls and guardrails
• Strong analytical and critical-thinking skills to evaluate AI/data use cases, models and data flows and propose mitigations
• Excellent communication, facilitation and stakeholder-management skills

• Excellent communication
• Stakeholder management
• Influencing both technical and non-technical audiences
• AI/ML/data science foundations
• Responsible AI and governance
• Model risk management and AI assurance

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