Artificial Intelligence

• Act as the go-to AI resource for your assigned team by meeting with stakeholders, understanding their workflows and pain points, and identifying where AI can provide practical value
• Triage incoming AI requests and determine the right path forward, whether that’s building a quick solution yourself, guiding someone to do it, or escalating to the broader AI or platform team
• Design and build low-code AI solutions such as prompts, workflows, agents, and rapid prototypes, then test, iterate, and refine them based on real user feedback
• Lead working sessions and provide hands-on coaching to help teams adopt AI tools, improve how they work, and build their own solutions with confidence
• Analyze AI usage and adoption trends to identify where teams are getting stuck and proactively deliver targeted support and enablement
• Contribute to firm-wide AI initiatives by collaborating with other AI Coaches, supporting internal programs and content, and helping execute trainings, events, and workshops
• Continuously stay current on emerging AI tools and capabilities while expanding your own skill set and sharing best practices across the firm

AI Coach – AI Enablement, Adoption

• Own the full AI engagement arc from discovery through sustained workflow adoption
• Drive requirements and delivery precision to track against plans and surface risks early
• Champion continuous quality through testing and feedback loops during AI engagements
• Hold the R&D feedback loop accountable to ensure field learnings flow back
• Build playbooks to identify reusable patterns and scalable frameworks for the team
• Own engagement economics and track cost structure across active engagements
• This is a field-first role with expected travel to partner locations

AI Engagement Manager

• Leading development-focused AI initiatives, taking ownership of key projects from prototyping through to execution and leveraging personal initiative to drive progress
• Building, managing, and mentoring a high-performing team of AI specialists, fostering a culture of innovation, collaboration, and continuous learning
• Operating with a high degree of autonomy while ensuring alignment with strategic direction received from executive leadership
• Developing, owning, and championing the organization's AI product technology roadmap, ensuring it aligns with broader business objectives
• Driving the flawless execution of priorities set forth by the leadership team
• Driving a strategic and transformational approach for integrating next-generation AI into our products and platforms
• Frequently representing the company's AI technology positions and priorities with external partners, research institutions, and public-facing entities
• Identifying and recommending technology partnerships to drive product value, collaborating with internal teams to formalize these partnerships
• Proactively managing executive-level meetings through briefing materials, clear positions, and status updates on AI strategy and innovation
• Providing frequent guidance, feedback, and prioritization to a diverse team with complex technical assignments
• Driving financial discipline related to AI technology acquisition and implementation

Associate Director – AI Product Development

• Provide critical expertise in AI-driven workforce development
• Act as the primary AI subject matter resource for the Responsible Business group
• Conduct assessments to identify job training needs related to AI fluency
• Curate, vet, and validate educational programs and external partner curriculums
• Collaborate with external partners for accurate delivery of AI skilling content
• Analyze performance toward defined goals and recommend changes
• Partner with internal Business Intelligence team for measurement framework
• Continuously monitor the field for emerging gaps in AI education
• Represent Verizon in external engagements or partnerships

Senior Manager, AI Workforce Development

• Leads ORM / ERM‑wide efforts for the Fraud, Insider and Conduct Risk Management team
• Responsible for the design, development, and curation of complex presentations, reports, dashboards, and scorecards
• Supports the integration of Artificial Intelligence (AI), including Generative AI
• Partner closely with senior leadership on high‑impact initiatives
• Drive the streamlining, health, and simplification of the reporting stack and related Risk processes
• Provide domain‑level expertise and risk‑based support for testing and quality assurance
• Manage relationships within and across various business lines to ensure alignment with enterprise and/or regulatory requirements

Senior Manager, Fraud Risk Analytics – AI Oversight

• 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

• Design, develop, and deploy AI Agent workflows using LLM-based orchestration frameworks (LangChain, AutoGen, CrewAI, or similar).
• Integrate LaunchDarkly for feature flagging, progressive rollouts, and experimentation across AI-enabled features.
• Implement comprehensive telemetry, logging, distributed tracing, and monitoring for AI agent systems.
• Build and maintain A/B testing and experimentation frameworks to evaluate agent performance and model outputs.
• Develop REST and event-driven integrations to connect AI agents with enterprise data sources and downstream systems.
• Author technical documentation including agent design specs, integration guides, and architecture deliverables.
• Participate in sprint ceremonies, contribute to backlog grooming, and deliver iteratively within an Agile framework.
• Support incident response, root-cause analysis, and continuous improvement for production AI systems.

AI Engineer

• Demonstrate advanced expertise in AI and lead detailed discussions with technical and business stakeholders
• Engage confidently with senior and C-level leaders and orchestrate complex opportunities across internal and external teams
• Influence and guide deal strategy, partnering closely with account executives to support territory planning, pipeline creation, opportunity progression, and forecasting
• Drive field execution of programs across the Genesys AI portfolio including sales campaigns and enablement initiatives
• Serve as a trusted subject matter expert and model best practice sales motions that elevate capability across the wider team
• Provide hands on support for positioning, presentations, pricing, proposals, and other key materials related to Genesys AI and Experience Orchestration
• Lead customer workshops that shape AI use cases, prioritisation frameworks, and pilot opportunities
• Act as the voice of the customer by capturing insights and partnering with cross functional teams in marketing, product, customer success, and professional services
• Identify strategic priorities and develop AI led opportunity pathways aligned to customer objectives
• Ad-hoc duties as required by management

AI and Experience Orchestration Director – Sales Overlay

• Lead stakeholders through process mapping and operational improvement
• Own the design, build, and iteration of low-code and AI-enabled workflows
• Translate business needs into reliable, production-grade automations
• Develop and maintain evaluation sets, define quality thresholds, and run A/B tests
• Integrate automation into dashboards and reporting
• Track and communicate impact of automation and AI solutions
• Continuously assess new and existing applications and SaaS platforms
• Lead pilots and proofs of value for new workflows or AI capabilities
• Provide training and enablement to Legal & Compliance teams
• Partner with the Compliance Training team to create AI use case specific policies

Data & AI Operations Manager

• Architect internal productivity revolution and analyze workflows.
• Rapidly prototype and refine agentic solutions.
• Help build and deploy production grade AI agents.
• Integrate AI agents with enterprise resources.
• Define and track productivity & ROI.
• Stay at the forefront of AI developments in the media industry.

Director, Applied AI – Strategy

• Own the Knowledge Layer: Architect and maintain the core troubleshooting logic, decision trees, and diagnostic maps for smart home devices, connectivity, and ISP environments.
• Define AI Interaction Flows: Design precise AI triage mechanisms, seamless escalation paths, and structured support playbooks that feel natural and effective to the end user.
• Optimize AI Performance: Partner directly with R&D and LLM Engineering to refine prompts, retrieval quality (RAG), and agent decision accuracy.
• Continuous Quality Assurance: Audit live customer-to-AI interactions to identify gaps, refine logic, and continuously improve the AI's real-world resolution rate.
• Standardize & Train: Set performance evaluation benchmarks and build training frameworks for internal teams and BPO partners.
• Voice of the Customer: Act as the internal champion for practical field support, translating real technician and consumer realities into engineering requirements.

Principal Domain Expert – AI Home Support & Connectivity

• Develop and execute an enterprise digital strategy aligned to RayzeBio's business objectives, driving operational efficiency, smarter decisions, and cross-functional collaboration.
• Lead digital transformation initiatives that modernize data and reporting, streamline workflows, and accelerate execution through automation and AI/ML where it creates tangible business value.
• Identify and prioritize high-impact opportunities to simplify the operating environment — reducing tool sprawl, minimizing friction, and improving speed without sacrificing quality or compliance.
• Own the enterprise analytics and AI/ML roadmap, prioritizing practical use cases across research, development, manufacturing, and commercial readiness.
• Oversee advanced analytics capabilities — including predictive modeling, forecasting, and machine learning — to support data-driven decision-making across functions.
• Establish fit-for-purpose data governance, ensuring data quality, integrity, security, and cross-functional accessibility.
• Bring an external perspective on emerging technologies and translate them into pragmatic, adoption-ready tools and approaches that RayzeBio teams can and will use.
• Partner closely with Research and Drug Development leadership to leverage data, analytics, and AI across the drug development lifecycle — from discovery and translational science through clinical development and CMC.
• Improve how data is captured, integrated, and used across preclinical, clinical, and manufacturing interfaces to increase insight quality, reproducibility, and execution readiness.
• Enable practical analytics and AI use cases that support development execution — including trial planning, study performance visibility, and decision support — while remaining compliant and fit for purpose.
• Lead data and analytics capabilities supporting commercial readiness and launch execution, including forecasting, scenario modeling, and performance analytics aligned to demand, supply, and revenue planning.
• Enable commercial teams with the tools, infrastructure, and insights needed to support go-to-market execution, customer engagement, and post-launch optimization.
• Partner closely with Commercial, Medical Affairs, Manufacturing, and Supply Chain to ensure analytic and technology readiness for launch and scaled commercialization.
• Own RayzeBio's technology ecosystem — infrastructure, applications, collaboration tools, and data platforms — ensuring scalability, security, and compliance.
• Ensure technology decisions are practical and user-centered — prioritizing adoption and real-world utility over technical sophistication for its own sake.
• Partner with BMS IT, analytics, and data organizations to leverage enterprise platforms while ensuring solutions remain tailored to RayzeBio's scale and operating model.
• Attract, develop, and retain top talent across data science, analytics, AI/ML, and technology; build a culture of innovation, ownership, and measurable impact.
• Lead effectively across a distributed, multi-site organization — driving clear priorities, transparent communication, and strong execution rhythms.
• Serve as a member of the RayzeBio leadership team; challenge assumptions, elevate thinking, and drive adoption of data-driven and AI-enabled ways of working across the organization.

Vice President, Data, Analytics, AI – Technology

• Provide Tier 1–2 support for Microsoft Copilot user issues (access, functionality, performance, unexpected responses, app integration concerns)
• Troubleshoot Copilot experiences across Microsoft 365 apps (e.g., Teams, Outlook, Word, Excel, PowerPoint) and related endpoints where Copilot is enabled
• Document incidents, resolutions, and known errors; contribute to problem management and root cause analysis trends
• Partner with the Service Desk to refine ticket categorization, routing, and standard troubleshooting scripts
• Create and maintain Copilot knowledge articles, FAQs, how-to guides, and troubleshooting playbooks
• Build and update prompt libraries and use-case guides tailored by function (HR, Finance, Merchandising, Supply Chain, IT, etc.)
• Collaborate with Microsoft 365 administrators, Identity/Access teams, Security, Legal/Privacy, and business stakeholders

Senior Administrator, Enterprise AI Tools End User Support

• Deliver data products and associated AI applications that are aimed at accelerating the Immunology R&D Pipeline
• Lead a team to develop technical requirements for Immunology-facing data products that enable AI applications
• Attract, upskill and retain top talents in the field, manage a technical team, and collaborate with key stakeholders in R&D, DSDH, and Johnson & Johnson Technology (JJT)
• Define and maintain a roadmap for Immunology data products, spanning discovery, translational research, clinical development, and real-world evidence
• Partner with Knowledge Management, Data Platforms & Governance, and Master Data Management teams to ensure Immunology data products integrate seamlessly into enterprise ontologies, knowledge graphs, and catalogs
• Lead a team that works with key business partners to develop and deploy impactful and scalable AI solutions for Immunology
• Contribute to the development and governance of an Immunology Ontology to enable semantic consistency across discovery, clinical, regulatory, and real-world data.

Senior Director, Immunology Data & AI Systems

• Establish and operate enterprise-wide governance, risk, and regulatory oversight for Data, AI, and Agentic AI
• Define and maintain enterprise policies, standards, and governance operating model for Data and AI
• Partner with each line of business to define and maintain the target state for Data and AI governance
• Own the enterprise inventory of AI initiatives across AI, GenAI, ML, and Agentic AI
• Act as the single enterprise point of contact for regulators, audit, and external inquiries related to Data and AI
• Monitor adherence to approval processes and continuously improve them to reduce friction and late-stage escalation

SVP, Data & AI Governance and Risk

• Find and Mitigate Risks in AI Projects as a Senior AI Analyst
• Leverage your skills and knowledge in AI systems to identify and assess potential risks and impacts, recommend appropriate mitigations, and prevent harm
• Work with business and technical stakeholders to understand business problems and AI risk
• Represent the global AI Ethics and Governance team - guide stakeholders on company governance processes and promote adoption of responsible AI
• Implement Explainable AI (XAI)
• Test and audit data sets, models and AI solutions for bias, fairness, and explainability using open-source and enterprise tools
• Support development and implementation of policy processes and further the field of AI ethics
• Research and stay on top of AI developments, best practices, and regulatory changes

Senior Artificial Intelligence Ethics and Governance Specialist

• Use-case prioritization across the full sales lifecycle
• Collaborate with Sales, Marketing, Operations, Enablement, Product, Legal and IT
• Define and track program indicators across AI proficiency, adoption velocity, workflow impact, and seller efficiency
• Monitor the external AI landscape — competitive deployments, emerging vendor capabilities, and agentic framework developments
• Own executive storytelling for All Hands, QBRs, and CRO forums
• Define current vs future-state architecture and tool landscape
• Lead strategic AI portfolio decisions including intake, prioritization, build-vs-buy evaluation, and deprecation for internal and third-party AI tools
• Operationalize AI governance standards across data usage, model risk, vendor selection, and responsible AI
• Define and implement the E2E change management and communications strategy for AI in Sales
• Lead the AI Ambassador Program to build grassroots momentum, drive adoption, and surface field-led guidelines back into the core program
• Design and roll out Adobe’s AI proficiency program for Enterprise Sales globally

Senior Manager, Enterprise AI Strategy

• 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

• Lead the evaluation and production readiness of AI products and capabilities across the enterprise.
• Ensure solutions are scalable, secure, governable, and aligned with enterprise architecture standards.
• Partner closely with Legal and Information Protection to meet regulatory and risk management requirements.
• Conduct GenAI intake reviews, applying enterprise AI guardrails and standards.
• Partner with solution teams and area technology leaders to clarify requirements and reduce redundancy.
• Steward enterprise AI architecture principles and requirements during path-to-production reviews.
• Advise cross-functional teams on solution architecture and data protection optimization.
• Serve as a strategic advisor on enterprise AI capabilities and opportunities.

Senior Architecture Advisor – AI Enablement

• 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

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