Artificial Intelligence

• Conduct research and analysis on the AI services and related broader services markets
• Deliver insightful and actionable advice to clients in a variety of roles within the high-tech industry
• Create innovative, thought provoking, and highly leveraged “must-have insights” content
• Develop new insights and ideas through thought leadership and offer compelling, actionable approaches to client's needs and requests
• Provide clients and prospects with actionable advice aligned to their designated content area

Senior Director Analyst – AI Services

• Lead a cross-functional product pod of Solution Consultants, Pega Configurators, and Business Analysts to deliver Pega-based workflow automation solutions aligned to business priorities.
• Provide day-to-day product direction, delivery oversight, mentorship, and issue resolution support to help the team meet commitments and maintain high execution standards.
• Own solution delivery from discovery and design through configuration, testing, deployment, and post-implementation feedback, with a focus on quality, usability, scalability, and control readiness.
• Work hands-on within Pega App Studio and Dev Studio to support solution design, configuration, testing, and implementation of workflow capabilities.
• Partner with architecture and engineering teams to ensure solutions align with platform architecture, technical standards, security requirements, and software delivery lifecycle expectations.
• Translate operational pain points, process inefficiencies, and business needs into clear product requirements, workflow designs, user stories, acceptance criteria, and delivery plans.
• Partner directly with operational leaders and business stakeholders to assess opportunities, shape solution options, manage expectations, and drive alignment on scope, priorities, benefits, and delivery timelines.
• Establish and monitor success measures for delivered solutions, including adoption, operational efficiency, user experience, quality, risk reduction, and other relevant business outcomes.
• Elevate product management practices across the team by improving intake, prioritization, roadmap planning, stakeholder communications, and outcome measurement.
• Identify and help resolve risks, issues, impediments, and dependencies that could impact delivery quality, control effectiveness, or business outcomes.
• Foster a collaborative, inclusive, and accountable team environment that supports talent development, clear communication, continuous improvement, and operational excellence.

Pega Product & Solution Delivery Lead – AI Case Management

• Drive enterprise-wide adoption of AI tools and workflows across departments.
• Partner with business leaders to identify operational inefficiencies and opportunities for AI integration.
• Develop and implement AI-driven process improvements that enhance productivity and reduce manual work.
• Act as an internal consultant to business teams on AI use cases and workflow optimization.
• Help establish AI best practices and promote responsible AI usage across the organization.
• Collaborate with cross-functional departments to translate business needs into scalable AI solutions.
• Help manage organizational change related to AI implementation and workflow transformation.
• Build resources, documentation, and SOPs related to AI usage and processes.
• Lead the implementation and optimization of AI tools and platforms.
• Track and report on AI initiative outcomes, adoption metrics, productivity improvements, and operational impact.
• Help ensure AI usage aligns with company policies, compliance requirements, and operational goals.
• Maintain organized documentation related to AI initiatives, workflows, and training materials.

AI Enablement Manager

• Configure and maintain Copilot using the Microsoft 365 Admin Center and Copilot Control System
• Execute day-to-day system settings, feature toggles, and configuration updates as directed by IT leadership
• Ensure Copilot operates reliably, securely, and in alignment with defined policies
• Manage Copilot license allocation and revocation using security groups
• Monitor license utilization via the Copilot Dashboard
• Identify and flag underutilized licenses for reallocation
• Implement sensitivity labels, access controls, and SharePoint permissions aligned with governance frameworks
• Identify and remediate overly permissive access that may expose sensitive data through Copilot
• Support enforcement of data protection and compliance standards within M365
• Monitor Copilot usage telemetry and generate regular reports for IT leadership
• Track license counts and contract renewal timelines
• Identify trends, anomalies, and adoption gaps
• Surface recommendations while deferring architectural and vendor decisions to leadership
• Monitor usage of secondary AI tools (e.g., ChatGPT Business for marketing) against acceptable use policies
• Escalate policy violations or data handling concerns to management
• Support deployment of custom AI agents in Copilot Studio, including testing configurations and verifying access controls
• Document deployment procedures and technical processes

M365 Administrator – AI

• Serve as a main technical voice for your account team
• Build deep, trusted relationships with C-suite and technical stakeholders
• Demonstrate how Salesforce's capabilities complement OpenAI's models
• Take ambiguous business problems and apply AI-first mindset
• Guide customers through solution evaluation and analysis
• Conduct deep-dive discovery with engineering, IT, and business teams
• Design and deliver compelling product demonstrations
• Orchestrate cross-functional solution teams
• Maintain understanding of the current AI competitive landscape
• Act as a feedback loop between OpenAI and Salesforce’s Product organization

Lead Account SE, Strategic AI

• Set the multi-year strategy for ML, data, and BI
• Build and scale the Data Science / AI, Data Engineering, and BI Engineering organization
• Manage managers and tech leads
• Run performance management, career development, and retention
• Operate as a peer to VP-level leaders across various functions
• Own the architecture, deployment, and operation of the production ML

VP of AI, ML and Data Strategy

• Lead a team responsible for identifying, designing, and executing AI and automation solutions
• Lead a team of approximately 10 automation professionals
• Ensure high-quality delivery and effective support for internal stakeholders
• Oversee identification and definition of AI and automation solutions aligned to business strategy
• Review and guide design recommendations
• Provide hands-on design direction for complex initiatives
• Partner with delivery, engineering, and architecture teams
• Serve as a senior liaison between business leaders and technical teams
• Guide evaluation of emerging AI and automation technologies

Operations Manager – AI & Automation Design

• Lead one or more AI solution deployments concurrently, including Workday AI products and acquired solutions
• Own end-to-end delivery execution, ensuring on-time, on-budget, and high-quality implementations
• Partner with Consulting, Product, and Customer AI teams to triage and resolve issues related to model performance
• Present at Executive Steering Committees, providing transparency on AI risks
• Support pre-sales activities as requested
• Coach and mentor Workday and partner resources in AI deployment practices
• Contribute to the ongoing evolution of the Workday AI Delivery Framework
• Facilitate the transition from deployment to steady-state operations

Senior Engagement Manager, AI Solutions Delivery

• Builds and/or executes business initiatives and/or processes, while partnering with stakeholders and partners.
• Solves complex problems and delivers on business initiatives and processes by applying subject matter expertise and technical knowledge of the business.
• Engages with key stakeholders, partners, and business leadership to deliver on business objectives.
• Performs analytics, assessments, and/or interpretation of data and/or information to identify business opportunities, derive insights, and measure outcomes.
• Develops strategic and tactical plans to drive progress towards business goals and objectives.
• Define, develop, and execute enterprise‑level initiatives that advance Client Servicing priorities, with a focus on AI‑enabled efficiency, operational performance, and measurable business outcomes.
• Lead the identification, coordination, and delivery of AI‑driven efficiencies across Client Services, ensuring initiatives are aligned, resourced, and governed effectively.
• Oversee multiple tactical deployments occurring simultaneously (AI, process optimization, workforce planning, etc.), ensuring prioritized sequencing, dependency management, and consistent execution discipline.
• Establish and enforce governance standards specific to AI‑related data usage within Client Services. Ensure controls, data quality, model inputs/outputs, reporting mechanisms, and risk management practices meet enterprise expectations.
• Maintain initiative scorecards, assess risks, track milestones, and drive corrective actions to protect delivery timelines and business outcomes.

Business Strategy & Initiative Manager – AI Horizontal Efficiencies

• Data collection, evaluation, and annotation.
• Pairwise comparisons.
• Counting tasks.
• Object tagging and labeling across different content types (audio, video, images, or collected data)

AI Data Specialist

• Develop and own the enterprise AI adoption strategy aligned with SupplyHouse's business objectives and long-term growth plans
• Identify high-impact AI use cases across procurement, operations, sales, customer service, and finance, and prioritize based on ROI and feasibility
• Serve as the primary internal authority on enterprise AI tools, platforms, and best practices including large language models, agentic workflows, and AI-powered analytics
• Monitor the AI technology landscape and advise executive leadership on emerging opportunities and risks
• Design and execute enterprise-wide change management programs grounded in proven methodologies to drive sustained, high-quality AI adoption across all levels and functions
• Act as a culture carrier for AI transformation championing a mindset of curiosity, continuous learning, and responsible experimentation throughout the organization
• Build internal champions, AI ambassadors, and center-of-excellence structures to scale AI literacy and usage across every business unit
• Develop training curriculum, playbooks, and role-based enablement programs to upskill employees on AI tools and workflows at every level, from frontline staff to senior leadership
• Create psychological safety around AI adoption by proactively addressing employee concerns about job displacement, skill gaps, and the pace of change positioning AI as a tool that augments human capability rather than replaces it
• Partner closely with the Human Resources team to embed AI competency into hiring profiles, onboarding programs, performance frameworks, and career development pathways
• Lead executive communications, all-hands presentations, and town halls related to AI strategy, adoption milestones, and organizational impact
• Identify and mitigate human-side risks of AI adoption including change fatigue, resistance patterns, and inequitable access to enablement resources across teams
• Partner with department heads across IT, Operations, Human Resources, Legal, and Finance to embed AI into core business processes
• Collaborate with the IT and Data Engineering teams to ensure secure, compliant, and scalable AI infrastructure
• Manage relationships with external AI vendors, consultants, and technology partners
• Coordinate with Legal and Compliance teams to establish responsible AI governance policies, data privacy standards, and risk frameworks
• Define KPIs and success metrics for AI adoption initiatives and report progress to the C-suite and Board as needed
• Establish feedback loops and continuous improvement processes to optimize AI tool performance and user experience
• Build business cases and ROI models to justify AI investments and scale successful pilots enterprise-wide
• Build, lead, and mentor a high-performing team of AI program managers, analysts, and change agents
• Foster a culture of experimentation, curiosity, and responsible innovation within the team and across the organization

Director, Enterprise AI Adoption

• Provide strategic leadership and hands-on direction for the design, build, and governance of automation and AI solutions supporting the CTG organization
• Partner closely with CTG technology leaders, risk and governance stakeholders, enterprise architecture, security, data teams, and approved third-party vendors to deliver targeted automation and AI capabilities that improve efficiency, strengthen controls, and enable better decision making across CTG functions
• Accountable for oversight, governance, and driving execution of automation and AI solutions
• Define and lead the automation and AI strategy for the Corporate Technology and Governance organization
• Drive the design and delivery of automation and AI solutions supporting CTG functions
• Establish and maintain CTG‑specific standards, guardrails, and governance for automation and AI
• Oversee end‑to‑end solution delivery, including requirements definition, design, testing, deployment, and ongoing support
• Ensure appropriate controls are embedded in automation and AI solutions
• Coordinate with enterprise technology, risk, security, and data partners to ensure CTG automation and AI solutions comply with policies, standards, and supervisory expectations
• Evaluate platforms, tools, and vendor solutions relevant to CTG automation and AI needs
• Track performance, value realization, and risk indicators for CTG automation and AI initiatives
• Lead, develop, and retain a high‑performing team

IT Director I – Automation and AI

• Learn how teams across the business work (Customer Service, Operations, Merchandising, Marketing, Product, etc.) and identify high-impact opportunities where AI can help
• Partner with stakeholders to define problems clearly, map workflows, and estimate potential value and effort
• Research and evaluate AI tools and approaches (LLMs, copilots, workflow automation, search/RAG, lightweight agents) for business use cases
• Build and test small prototypes or proofs of concept (e.g.: prompt workflows, chat-based assistants, automation scripts, internal knowledge helpers)
• Create clear documentation and playbooks so others can reuse what you build (prompt guides, best practices, example workflows)
• Help run simple enablement activities like demos, office hours, training sessions, and collecting feedback
• Track results and learnings, including what worked, what did not, and recommendations for next steps
• Follow responsible AI practices, including data privacy, security, and quality standards

AI Enablement Intern

• Own end-to-end delivery for multiple enterprise customer engagements
• Partner with customers' C-level executives on AI strategy and transformation
• Lead one or more concurrent implementations, ensuring projects are delivered within the budget and timeline outlined in the statement of work
• Manage timelines, risks, and cross-functional coordination to ensure smooth delivery
• Identify retention opportunities and potential areas for expanded engagement
• Provide guidance and mentoring to Professional Services team members working on your implementations
• Identify and resolve issues that could affect project scope or timelines
• Participate in the sales cycle when requested to gather requirements, formulate delivery approaches, and develop proposals

Engagement Manager, AI Practice

• AI Solution Design & Development: Independently design and build complete AI solutions — agents, multi-step workflows, and integrations.
• Platform Configuration & Administration: Configure and manage AI platform environments including agent deployment, knowledge base architecture, data connector setup, access controls, and workspace organization.
• Data Orchestration & Integration: Connect, shape, and manage data pipelines between business systems (Salesforce, Totango, Jira, Redshift, Snowflake) and the AI platform.
• Technical Problem-Solving & Debugging: Independently diagnose and resolve complex issues across the AI solution stack.
• System Integration & Extensibility: Extend platform capabilities through available integration frameworks and develop custom connectivity solutions as needed.
• Workflow & Automation Development: Design and build automated workflows and multi-step processes within AI platforms.
• Program Champion Enablement: Partner with program champions embedded in Proofpoint's Services teams.
• Documentation & Knowledge Sharing: Create and maintain feature documentation, SOPs, capability guides.
• Business Consulting & Opportunity Identification: Proactively understand business workflows and identify AI opportunities.
• AI Landscape Evaluation: Track developments across the broader AI landscape and evaluate how emerging tools impact the team's work.
• Performance Monitoring: Monitor AI solution performance, identify improvement opportunities independently.

AI Integration Specialist

• Collaborates with key stakeholders to identify key business assumptions and hypotheses around line of business strategy.
• Continuously refines hypotheses and identifies business questions to explore further.
• Facilitates the integration of the analytic strategy and business strategy.
• Develops the analytical framework and blueprint to answer business questions identified in the business portfolio, product, or member experience.
• Collaborates with key stakeholders to evaluate and uncover strategic insights related to Profit & Loss performance including Product Strategy, Pricing, Marketing, Sales, Credit Risk, Distribution Channels, and Member Experience.
• Applies analytical rigor to define outcome measures, improve prioritization, increase agility in decisioning, improve ability to evaluate progress towards business outcomes, and to evaluate risks to strategic goals.
• Leverages advanced data-driven problem-solving techniques to manipulate and interpret business results.
• Translates findings into insights for strategy management and execution.
• Communicates the significance of strategic insights to senior leaders and other key stakeholders to drive business decisions.
• May provide guidance and on-the-job training to team members.
• Ensures risks associated with business activities are effectively identified, measured, monitored, and controlled in accordance with risk and compliance policies and procedures.

Senior Business Strategy Analyst – AI COE

• Leads control projects with broad scope and complexity within divisions
• Develops and implements internal control framework
• Identifies and remedies complex control gaps
• Provides expert level consulting on audit activities
• Leads and manages risk mitigation initiatives in response to audit findings
• Collaborates with internal and external stakeholders to communicate control solutions

AI and Data Controls Manager

• Own an enterprise portfolio of agentic AI use cases; shape multi-quarter roadmaps tied to business strategy, scalability and measurable outcomes; define success metrics (value, quality, portability) and manage trade-offs across initiatives.
• Define agentic framework to conduct end-to-end discovery (diagnostics, data/system constraints, user journeys) to identify high-value agentic opportunities; translate pain points into agentic AI solutions (tools/actions, guardrails, autonomous or human-in-the-loop) and delivery plans.
• Build and defend business cases (cost, revenue, CX improvement); secure executive alignment; establish benefits measurement (baseline, attribution, measurement) and manage realization through adoption and continuous improvement.
• Coordinate with cross-functional squads (product, AI engineering, data science, architecture, operations) and external partners to deliver pilots and scaled deployments; manage scope, dependencies, risks, and delivery quality; run executive steering and agentic AI program governance.
• Partner with Responsible AI leader to implement controls for data handling, model/vendor risk, explainability, and operational resilience; ensure appropriate guardrails (policy, content filtering, escalation paths) for production agent use.
• Lead launch planning, training, communications, and hypercare; drive stakeholder readiness and measurable adoption; establish feedback loops and a backlog for post-launch enhancements across business units.

AI Delivery Leader

• Provide comprehensive capacity building and compliance assistance to Alaska Native victim services programs to ensure compliance with DOJ/OJP award conditions, including client confidentiality policies, program narratives, time-task plans, and addressing award conditions
• Plan and execute assistance activities including developing and advancing customized assistance plans, sharing subject matter expertise, and reporting on outcomes
• Assist programs in developing or enhancing victim services policies and procedures, conducting community needs assessments, and developing strategic and sustainability plans
• Support recipients in resolving OJP monitoring issues and implementing corrective actions
• Evaluate individual grantee needs and partner with grantees to implement and track progress of customized assistance plans
• Work closely to support grantees as they enhance and strengthen their crime victim services
• Develop trainings, curriculum, and resources appropriate for Alaska Native audiences and their identified needs
• Facilitate trainings including webinars, peer learning exchanges and communities of practice
• Assist with strategic planning
• Conduct reviews of resources, infrastructure, and capacity within the grantee communities
• Identify and share culturally responsive, trauma informed practices, resources, and approaches

Project Specialist – AI/AN Victim Services Programs

• Own the workforce enablement approach for AI‑driven workflow and role changes
• Design and run enablement programs that drive real adoption — not “check‑the‑box” training
• Equip managers to lead teams through transition, including readiness, support, and tough conversations
• Translate redesigned workflows into clear role expectations, skills, and enablement plans
• Build practical toolkits, learning experiences, and manager resources that actually get used
• Partner across Talent, HR, and AI teams to ensure enablement comes before accountability shifts
• Track adoption using leading indicators (behavior change, readiness, friction), not vanity metrics
• Continuously refine approaches based on real signals from employees and managers

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