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# Cyber AI Governance and Privacy Consultant

- **Company:** Deloitte T.T.L.
- **Location:** Kansas City, MO, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Software Documentation, Cyber Security, Systems Development Life Cycle, Software Engineering, Systems Integration, Data Logging, Large Language Models
- **Published:** August 18, 2026
- **Apply:** https://www.kansasworks.com/jobs/13642429

## About the Role

+ 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

## Description

We are seeking an AI Governance and Privacy Consultant who can operationalize responsible AI in real systems-especially agentic AI and LLM-enabled applications. This role blends governance and privacy expertise with enough software development fluency to create developer-ready guidance, implement controls-as-code patterns, and stand up measurable evaluation and monitoring workflows.

As a Senior Consultant, you will help clients and internal delivery teams move from AI principles to practices: risk tiering, model and agent inventories, technical guardrails, governance workflows integrated into the SDLC, and evidence artifacts suitable for audits and regulators.

Recruiting for this role ends on 12/31/2026.

Work you'll do

As a Consultant, Strategy, Growth and Transformation on the Cyber team, you will be responsible for:

 + 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.


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