AI and Automation Advisor

Senior Consultant AI & Automation Advisory - Data Protection Services (DPS) Team: Solutions - AI & Automation Advisory Reports To: Lead Consultant or Senior Manager, AI & Automation Advisory Role OverviewThe Senior Consultant - AI & Automation Advisory is a skilled individual contributor who owns defined delivery tasks and workstream components within WWT's AI & Automation Advisory practice, supporting engagements such as the Client's Data Protection Services (DPS) AI Efficiency Assessment. Positioned below the Lead Consultant, the Senior Consultant brings hands-on depth across AI opportunity assessment, process and workflow analysis, and data protection domain knowledge, executes high-quality client deliverables with growing independence, and begins developing trusted client relationships at the working level. The Senior Consultant is the engine of AI advisory delivery - leading current-state discovery across data protection pillars and functions, identifying and cataloguing AI-enabled use cases, supporting feasibility and target-state operating model design, and producing the analytical outputs that underpin client recommendations. They work under the direction of a Lead Consultant, Principal, or Senior Manager, and are expected to grow steadily toward owning full workstreams and contributing to pre-sales activities. What is Expected Engagement Delivery Execute assigned delivery tasks and workstream components within AI efficiency assessment engagements with accountability for quality, accuracy, and on-time completion Lead technical components of the assessment: conduct current-state discovery across Data Protection Fleet pillars (Cryptography and Secrets, Data Leakage Prevention, Data Asset Protection) and horizontal functions (Policy and Architecture, Fleet Enablement, Development, Engineering), document findings, and identify opportunity themes with guidance from the engagement lead Perform hands-on AI opportunity work: use-case identification, process and workflow mapping, agent design input (guided, pillar-specific, and cross-pillar orchestration agents), feasibility scoring, and prioritization support Produce client-ready deliverables - current-state assessment packs, AI opportunity inventories, use-case catalogues, target-state operating model inputs, roadmap inputs, and executive summaries - that meet WWT's professional services quality standards Facilitate discovery sessions, stakeholder interviews, and working-level workshops with DPS pillar and function stakeholders; synthesize findings into structured outputs for Lead Consultant review Maintain the DPS AI Initiatives Tracker workbook as the engagement's system of record, including entries in the Innovation Backlog, AI Initiatives Register, AI Risk and Controls, and AI Benefits Tracking sheets, and support classification of implementation status and validation of Jira AI labeling Client Engagement Build working-level relationships with DPS pillar and function stakeholders, technology teams, and project sponsors; establish credibility as a reliable, knowledgeable AI advisory resource throughout the engagement Communicate findings clearly and accurately to client counterparts; begin developing the ability to present findings to project sponsors and working-group leadership Contribute to client status reporting, meeting facilitation, and action item tracking under the direction of the engagement lead Pursuit & Practice Support Support pre-sales and pursuit activities: contribute to SOW scoping, effort estimation, and proposal content for AI and automation advisory engagements under the direction of the Lead Consultant or Senior Manager Contribute to practice development through reusable delivery assets, AI opportunity assessment templates, use-case catalogues, and technical write-ups Begin developing commercial awareness: understand engagement economics, utilization expectations, and how delivery quality connects to client satisfaction and account growth Growth & Development Actively build depth across AI/automation domains, agentic architectures, and data protection frameworks through project work, certifications, and self-directed learning Seek and apply feedback from Lead Consultants and Senior Managers; demonstrate consistent growth in delivery independence, communication quality, and domain breadth Begin supporting and coaching more junior colleagues on technical tasks and WWT delivery standards QualificationsRequired 4-8 years of experience in AI/automation strategy, technology consulting, or process engineering with a clear focus on AI-enabled efficiency, agentic solutions, or workflow automation; experience in cybersecurity, data protection, or regulated enterprise environments strongly preferred Hands-on experience across AI advisory domains and platforms, including one or more of: AI Opportunity Assessment - current-state process/workflow discovery, use-case identification, feasibility and control-readiness assessment, prioritization frameworks, and business case development Agent & Automation Design - enterprise agent and productivity platforms (M365 Copilot, Copilot Studio, Agent Builder, Power Automate + AI, Power Citizen), developer coding assistants (GitHub Copilot, Claude Code, Amp), and orchestration/human-in-the-loop design AI Governance & Controls - responsible AI principles, model and agent lifecycle controls, risk and controls tracking, data sensitivity classification, and approval/audit alignment Data Protection & Cybersecurity Domain - exposure to cryptography and secrets management, data leakage prevention (DLP), data asset protection/DSAR workflows, or security policy and architecture, particularly within regulated or financial services environments Initiative Tracking & Reporting Platforms - experience with workbook- or Jira-based initiative tracking, KPI/benefits tracking, and executive dashboard reporting Working knowledge of AI and data protection frameworks: responsible/trustworthy AI principles, NIST AI RMF, enterprise SDLC and engineering standards, and data protection concepts spanning cryptography, secrets management, DLP, and data asset protection Understanding of core AI advisory concepts: AI category taxonomies (Automate, Assist, Augment, Generate, Analyze), lifecycle stages (Idea/Concept through Deployed/Scaled), human-in-the-loop design, feasibility vs. desirability vs. viability, and control readiness in regulated environments Demonstrated consulting delivery competencies, including: Structured discovery: ability to conduct current-state discovery interviews, gather documentation and workbook/Jira evidence, manage information collection across pillars and functions, and synthesize findings into clear, structured outputs Opportunity and gap analysis: experience assessing operating-model maturity against AI adoption criteria, documenting opportunity and control gaps, and prioritizing findings by business impact and feasibility Technical communication: ability to translate AI opportunity and data protection findings into clear written deliverables and verbal summaries for technical and working-level client audiences Workshop facilitation: participate in and contribute to discovery sessions, opportunity-identification workshops, and validation sessions; begin developing the ability to facilitate independently Deliverable quality: consistent track record of producing accurate, well-structured client deliverables - assessment packs, use-case catalogues, workbook updates, and roadmap inputs - on time and to standard Engagement collaboration: work effectively within project teams; communicate status, risks, and issues proactively to the engagement lead; adapt to shifting priorities and client needs Preferred Bachelor's degree in Computer Science, Information Security, Data Science, Business, or a related field Certifications demonstrating AI, automation, or security knowledge: Microsoft Certified: Copilot or related AI credentials, CISSP, CISM, CISA, PMP, or equivalent Experience in enterprise environments across financial services, healthcare, or other regulated sectors - particularly where AI adoption intersects with cybersecurity, data protection, or regulatory scrutiny Prior consulting experience at a professional services firm, systems integrator, or equivalent client-facing advisory role Familiarity with pre-sales processes: SOW development, effort estimation, or proposal support for AI/automation advisory engagements Key Competencies AI/automation domain depth and hands-on opportunity assessment execution Delivery quality and individual accountability Clear technical communication - written and verbal Collaborative team contributor with a growth orientation Success in this role means executing AI efficiency assessment deliverables with high quality and growing independence, building credibility with client teams through consistent performance, expanding domain depth across AI advisory and data protection, and contributing to a practice that clients trust and return to - while building toward the skills and experience required to step into a Lead Consultant role. 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