Cyber AI Governance and Privacy Senior Consultant
- Designing and implementing AI governance operating models, intake workflows, risk tiering, approvals, documentation standards, exception handling, and audit-ready evidence processes for generative AI and agentic AI deployments.
- Building and maintaining inventories for models, agents, tools, data sources, and integrations, with defined ownership, intended use, risk classification, and change-control requirements.
- Conducting risk assessments across privacy, security, model risk, and misuse scenarios, including prompt injection, sensitive data exposure, excessive agency, and overreliance, and translating findings into implementable mitigations.
- Establishing technical control guidance for teams building agentic AI solutions, including human-in-the-loop patterns, tool access controls, retrieval and grounding practices, logging, monitoring, token and data minimization, and incident response playbooks.
- Integrating governance checkpoints into product and engineering delivery through architecture reviews, release gates, evaluation requirements, documentation automation, evidence capture, dashboards, and cross-functional collaboration with Cybersecurity, Privacy, Legal, Risk, Engineering, and Data Science teams.
- Ability to work independently and collaborate as part of a team
- Effective written and verbal communication skills
- Meticulous attention to detail and quality of work product
- Ability to build and sustain professional relationships
- Ability to lead projects or workstreams
- Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
- Strong interpersonal skills and professional demeanor
- Ability to meet deadlines
- Ability to provide clear guidance to others
- Bachelor's degree or equivalent practical experience.
- 4+ years of experience in AI governance, data privacy, security risk management, compliance and controls, AI product risk, model risk management, or technology risk consulting.
- Experience translating policies and regulatory expectations into operational workflows and artifacts, including intake processes, inventories, decision logs, risk registers, responsibility assignment matrices, playbooks, privacy impact assessments, and data protection impact assessments.
- Experience assessing AI, machine learning, and LLM deployment patterns, including training, retrieval-augmented generation, fine-tuning, tool use, data dependencies, and integration patterns, and defining mitigations for privacy, security, model risk, and misuse.
- Experience prototyping or automating governance workflows using Python or Structured Query Language and working with continuous integration and continuous deployment pipelines and cloud deployment basics.
- Ability to travel 0-50%, on average, based on the work you do and the clients and industries/sectors you serve.
- Limited immigration sponsorship may be available.
- Experience in consulting or a Big 4 environment.
- Experience operationalizing AI governance aligned to the National Institute of Standards and Technology AI Risk Management Framework or ISO/IEC 42001.
- Experience with generative AI safety and evaluation practices, including prompt injection testing, jailbreak resilience, hallucination measurement, toxicity scoring, harm scoring, and grounding effectiveness.
- Experience with governance, workflow, or ticketing platforms, including OneTrust and governance, risk, and compliance systems, and integrating those platforms into engineering delivery processes.
- Certifications such as Certified Information Privacy Professional/United States, Certified Information Privacy Manager, International Association of Privacy Professionals AI Governance Professional, Certified Information Security Manager, or Certified Information Systems Security Professional.
- Experience in cyber or enterprise security environments, including data security, identity, audit logging, secure software development lifecycle practices, human-in-the-loop escalation pathways, exception handling, and automated safety protocols for autonomous systems.
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