AI Governance & Data Privacy General Counsel

Honeywell Honeywell · Industrial · Charlotte, NC +1

Seeking an experienced AI Governance & Data Privacy General Counsel to provide strategic legal guidance on AI innovation, data privacy, and enterprise risk management, enabling responsible AI adoption and compliance across internal operations, products, and third-party solutions in a highly regulated environment. Responsibilities include leading AI governance strategy, developing policies, advising on data governance for AI/ML, supporting AI contracting, and managing global privacy and data protection for business units.

What you'd actually do

  1. Lead and execute Honeywell’s AI governance and legal strategy, maintaining and operationalizing Honeywell’s scalable Responsible AI Governance Framework to enable growth and innovation while managing risk.
  2. Develop, maintain, and advise on the implementation of AI governance policies, standards, and processes under applicable regulations, including algorithmic accountability, model validation, bias testing, human-in/on-the-loop requirements, monitoring, testing, inventory management, and decommissioning of AI systems.
  3. Provide legal oversight of AI marketing and external capability claims to ensure accuracy, consistency, and avoidance of misleading statements or “AI washing.”
  4. Advise on data governance for AI/ML systems, including lawful basis/consent, data quality and provenance, privacy-enhancing techniques, retention, and access controls for training, fine-tuning, evaluation, and monitoring datasets.
  5. Provide legal support for AI contracting, procurement, and third-party diligence, including developing standard customer and supplier terms and addressing AI risk considerations in commercial transactions and M&A.

Skills

Required

  • 10+ years of relevant legal experience, including significant experience advising on AI, privacy/data protection, and technology matters.
  • J.D. (or equivalent) and admitted to practice law in a jurisdiction in the United States.
  • Established thought leader on AI law and governance, data privacy, and complex technology regulatory risk areas, with a demonstrated ability to influence at the senior leadership level.
  • Deep working knowledge of global AI, data privacy, and data protection regulations.
  • Proficiency partnering with technical teams on security and resilience, accuracy and robustness evaluation, bias and fairness assessment, explainability and transparency practices, and appropriate governance processes and artifacts.
  • Ability to define success criteria using KPIs, dashboards, and risk heat maps to assess risk and propose effective mitigation strategies.
  • Strong contracting capability for AI and data, including drafting and negotiating AI- and privacy-specific terms (data use restrictions, audit rights, security requirements, IP, and allocation of AI-related risk).
  • Incident response and regulatory engagement experience for AI- and privacy-related events, including investigations, audits, and interactions with regulators globally.

Nice to have

  • Experience with GDPR, CCPA/CPRA, LGPD, PIPL, cross-border transfer laws, and other sectoral and state privacy laws.
  • Experience leading and advising on Data Protection Impact Assessments (DPIAs), risk assessments, and other privacy reviews.
  • Experience drafting, reviewing, and negotiating privacy and data protection terms (DPAs, SCCs, cross-border transfer mechanisms, security addenda, and audit rights).
  • Experience partnering with cybersecurity and incident response teams on privacy incidents and data breaches.
  • Experience overseeing privacy compliance for marketing, digital analytics, and customer engagement activities.
  • Experience developing and delivering privacy training and awareness for business and technical stakeholders.

What the JD emphasized

  • AI Governance
  • Data Privacy
  • regulatory guidance
  • risk management
  • responsible AI adoption
  • AI policies
  • algorithmic accountability
  • model validation
  • bias testing
  • human-in/on-the-loop requirements
  • monitoring
  • testing
  • inventory management
  • decommissioning of AI systems
  • AI marketing
  • AI washing
  • data governance for AI/ML systems
  • lawful basis/consent
  • data quality and provenance
  • privacy-enhancing techniques
  • retention
  • access controls
  • training datasets
  • fine-tuning datasets
  • evaluation datasets
  • monitoring datasets
  • AI contracting
  • procurement
  • third-party diligence
  • customer terms
  • supplier terms
  • commercial transactions
  • M&A
  • AI literacy initiatives
  • Responsible AI Governance Framework
  • enterprise-wide training
  • function-specific training
  • awareness campaigns
  • senior leadership
  • AI policy trends
  • regulatory risk
  • contractual risk
  • reputational risk
  • AI-related incident response
  • escalation
  • legal
  • cybersecurity
  • engineering
  • HR
  • communications teams
  • litigation involving AI technologies
  • external forums
  • industry groups
  • standards bodies
  • global privacy
  • data protection
  • GDPR
  • CCPA/CPRA
  • LGPD
  • PIPL
  • cross-border transfer laws
  • sectoral and state privacy laws
  • Data Protection Impact Assessments (DPIAs)
  • risk assessments
  • privacy reviews
  • new products
  • AI use cases
  • third-party tools
  • remediation plans
  • risk acceptance
  • privacy and data protection terms
  • DPAs
  • SCCs
  • cross-border transfer mechanisms
  • security addenda
  • audit rights
  • customers
  • suppliers
  • strategic partners
  • privacy incidents
  • data breaches
  • regulatory notification analysis
  • communications strategy
  • post-incident corrective actions
  • marketing
  • digital analytics
  • customer engagement activities
  • cookies/trackers
  • consent management
  • targeted advertising
  • privacy notices
  • data subject rights workflows
  • internal operating procedures
  • audits
  • regulator inquiries
  • outside counsel
  • privacy training
  • awareness
  • business stakeholders
  • technical stakeholders
  • product lifecycle
  • procurement processes
  • AI law
  • complex technology regulatory risk
  • influence at the senior leadership level
  • global AI
  • data privacy
  • data protection regulations
  • technical teams
  • security
  • resilience
  • accuracy
  • robustness evaluation
  • bias
  • fairness assessment
  • explainability
  • transparency practices
  • governance processes
  • artifacts
  • success criteria
  • KPIs
  • dashboards
  • risk heat maps
  • risk mitigation strategies
  • AI contracting
  • data contracting
  • drafting
  • negotiating
  • AI-specific terms
  • data use restrictions
  • audit rights
  • security requirements
  • IP
  • allocation of AI-related risk
  • incident response
  • regulatory engagement
  • AI-related events
  • investigations
  • audits
  • regulators globally
  • 10+ years of relevant legal experience
  • advising on AI
  • privacy/data protection
  • technology matters
  • J.D. (or equivalent)
  • admitted to practice law in a jurisdiction in the United States