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Tech Stack
Tools & technologiesPython
About the role
Key responsibilities & impact- Lead and deliver AI Governance and Responsible AI engagements, ensuring high quality outcomes within timelines and budgets
- Advise clients on embedding Responsible AI principles across the AI lifecycle—from ideation and design to deployment and monitoring
- Design, assess, and implement AI governance frameworks, policies, standards, and operating models
- Perform AI use case–level risk assessments, identifying ethical, regulatory, operational, model, data, and technology risks
- Define risk and control matrices (RCMs) for AI/ML systems aligned to leading frameworks and regulations
- Test the design and operating effectiveness of AI controls, including governance, model risk, data, security, and monitoring controls
- Conduct root cause analysis for AI-related issues and incidents and guide clients on practical remediation solutions
- Develop clear, actionable recommendations and executive ready reports for senior stakeholders
- Support clients in operationalizing Responsible AI beyond principles—into processes, controls, tools, and metrics
- Assess AI/ML systems including traditional ML and Generative AI / Agentic AI applications
- Guide clients on model risk management, human in the loop controls, explainability, bias mitigation, and monitoring
- Stay current on evolving AI regulations, standards, and best practices (e.g., EU AI Act, ISO 42001, NIST AI RMF, OECD)
- Manage day to day client relationships and act as a trusted advisor to senior client stakeholders
- Lead, mentor, and develop team members; review work products and provide constructive feedback
- Actively contribute to practice growth, solution development, thought leadership, and go to market initiatives
Requirements
What you’ll need- 5+ years of experience in Risk Advisory, AI Risk, Technology Risk, Internal Audit, or AI/ML roles within Big 4 or comparable consulting/technology environments
- Hands on Responsible AI implementation experience (non negotiable)—either from a risk/governance or AI/ML execution perspective
- Proven experience in one or more of the following: AI Risk Management & Governance, Responsible AI operationalization, AI/ML model risk assessments, Root cause analysis and remediation design
- Strong understanding of AI systems, data pipelines, and AI deployment lifecycles
- Bachelor's or Master’s degree in Engineering, Computer Science, Risk Management, or a related field
- Good to have Professional certifications such as AIGP, ISO 42001, CISA, CISM, CRISC, CISSP, ISO 27001, or similar
- Working knowledge of Python, ML concepts, or AI tooling to assess implementations effectively
Benefits
Comp & perks- Exposure to market leading AI governance and Responsible AI engagements
- An environment focused on learning, coaching, and career progression
- Opportunities to work with global clients and cutting edge AI use cases
- Flexibility, collaboration, and a culture built on trust and inclusion
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
AI GovernanceResponsible AIAI Risk ManagementAI/ML model risk assessmentsRoot cause analysisData pipelinesAI deployment lifecyclesPythonML conceptsGenerative AI
Soft Skills
LeadershipMentoringClient relationship managementCommunicationProblem-solvingAnalytical thinkingConstructive feedbackAdvisory skillsTeam developmentStakeholder engagement
Certifications
AIGPISO 42001CISACISMCRISCCISSPISO 27001