Artificial Intelligence

• 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

• The Director, AI Innovation & Emerging Capabilities leads the scouting, introduction, and scaling of AI and disruptive digital technologies across R&D.
• This role serves as the function's primary horizon scanner and innovation translator, converting external signals into concrete R&D opportunities and building structured pathways from early-stage pilots to scaled capabilities.
• The Director operates with a future-back mindset, ensuring the organization is not caught off-guard by technological disruption but instead positioned to capitalize on it.
• Continuously monitor the external AI and disruptive technology landscape to identify signals, trends, and emerging capabilities with potential R&D relevance.
• Maintain a living map of the external innovation environment including academia, startups, vendors, and adjacent industries.
• Establish and manage a network of external relationships (research institutes, technology partners, innovation ecosystems) to maintain leading-edge awareness.
• Triage and assess emerging threats and opportunities using structured evaluation frameworks before they surface in mainstream discourse.
• Translate complex external technology signals into concise, R&D-relevant opportunity briefs that leadership can act on.
• Identify and articulate capability gaps between the current R&D operating model and what disruptive trends demand.
• Introduce capabilities and approaches that would not organically surface through internal channels, deliberately expanding the organization's aperture of what is possible.
• Develop compelling narratives and business cases for disruptive capabilities, tailored to senior R&D and cross-functional audiences.
• Design and govern a structured pipeline from exploratory pilot to production-scale capability, with defined stage-gates, success criteria, and go/no-go decision logic.
• Lead proof-of-concept and pilot initiatives for high-potential disruptive technologies, ensuring rapid learning cycles and clear value demonstration.
• Partner with delivery and product teams to transition successful pilots into scalable, embedded capabilities that measurably improve R&D execution.
• Define and track performance metrics demonstrating that disruptive capabilities are delivering tangible, quantifiable impact on R&D outcomes.
• Provide R&D leadership with a clear, regularly updated view of the innovation landscape; presenting insights in formats that drive decision-making, not just awareness.
• Serve as a credible internal voice on AI and digital disruption, challenging conventional thinking and advocating for proactive capability investment.
• Contribute to strategic planning cycles by ensuring innovation foresight is embedded as a structural input, not an afterthought.
• Support team operating model design and contribute to intake and prioritization processes.

Director, AI Innovation – Emerging Capabilities

• Define and ship differentiated product capabilities for a prioritized set of customer and business use cases, with clearly documented success metrics (customer impact, adoption, revenue, efficiency, and risk reduction).
• Own the end-to-end product strategy and roadmap across platforms, applications, and AI-enabled capabilities, aligning firm-wide priorities and measurable outcomes.
• Establish scalable product operating models, including discovery, prioritization, roadmap governance, and delivery cadences across multiple product teams.
• Partner with Engineering and Architecture to ensure products are built on secure, resilient, and extensible platforms with clear technical and data foundations.
• Operationalize product lifecycle management including launch readiness, telemetry, adoption tracking, feedback loops, and continuous improvement.
• Hire, mentor, and lead a high-performing team of Product Managers across core platforms, workflows, and emerging AI capabilities.
• Partner with Knowledge Management, Data, and Engineering teams to translate domain workflows into product requirements, roadmaps, and prioritization frameworks.
• Work closely with Legal, Privacy, Security, and Compliance teams to ensure products meet confidentiality, regulatory, and risk management standards.
• Lead the full product lifecycle including problem framing, user research, requirements definition, delivery, launch, measurement, and iteration.
• Drive alignment across stakeholders including partners, business leaders, engineering leaders, and go-to-market teams.
• Establish and own product success metrics tied to customer outcomes, operational efficiency, and business performance.
• Lead change management and adoption efforts including training plans, playbooks, communications, and executive reporting.
• Publish and maintain product standards, decision frameworks, roadmap artifacts, and internal product guidance.

Director, Product AI – Platforms

• Lead the development and maintenance of the enterprise data domain model, taxonomy, and ontologies to ensure shared understanding, semantic consistency, and discoverability of data and knowledge assets.
• Design and evolve information and semantic models that make enterprise data AI‑ready, supporting use cases ranging from traditional analytics and BI to applied machine learning and LLM‑based experiences (e.g., search, retrieval‑augmented generation, and copilots).
• Operationalize data models, taxonomies, and semantic structures through the Enterprise Data Catalog (Alation).
• Define and enforce standards for data modeling, taxonomy, nomenclature, and semantic structures to ensure consistency and interoperability across business domains and downstream consumption patterns.
• Provide authoritative guidance on semantic conflicts—resolve definition discrepancies, harmonize terms, and mediate cross‑domain dependencies to establish trusted, reusable business meaning.
• Contribute to the enterprise data product framework by defining domain boundaries, shared dimensions, and semantic contracts that enable cross‑domain interoperability and AI consumption.
• Confirm and document prioritized metadata elements for key business processes, analytical use cases, and AI‑enabled workflows, ensuring alignment with governance standards and risk expectations.
• Identify simplification opportunities—reduce redundancy, converge overlapping datasets, and promote canonical sources to improve trust, efficiency, and reusability across analytics and AI platforms.
• Partner with analytics, data science, and AI engineering teams to ensure information architecture, metadata, and semantic context are sufficient to support explainable, governed, and trustworthy AI outcomes.
• Serve as a thought partner, provide insights from modeling, catalog adoption, and AI enablement to shape governance strategy and roadmaps.

Knowledge Architect

• 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

• designing, building, and shipping AI‑powered products and platforms
• embedding strong technology risk and control foundations from day one
• hands‑on engineering, integrating, and hardening modern AI stacks
• defining how AI products are built, deployed, and scaled safely across Fidelity

AI Technology Risk Engineer

• Develop AI/ML models to predict structural biomolecular interactions for novel modalities leveraging protein-protein interactions.
• Design innovative AI/ML approaches to predict protein cooperativity, affinity & other biological properties based on structures.
• Develop co-folding models that incorporate structural and non-structural priors using combinations of public and proprietary BMS data.
• Develop AI/ML models that leverage chemoproteomics data contributing to the generation of novel druggability hypotheses for hard-to-drug targets.
• Author scientific reports, and present methods, results, and conclusions to publishable standard.
• Contribute to the planning and execution of collaborative projects with leading academic and commercial research groups worldwide.

Senior Scientist, AI Computational Structural Biology

• Research and analyze AI's impact on marketing decision-making and execution cycles
• Write and produce content in various formats such as reports and podcasts
• Apply Forrester’s research frameworks to help clients solve business challenges
• Establish industry presence as a thought leader and influential speaker
• Evolve and productize marketplace coverage with sales and analyst relations

Principal Analyst – AI-Enabled Marketing

• Refine the ICP, pricing model, and product positioning across freight brokerages, 3PLs, carriers, and warehouse operators
• Lead pilots with mid-sized to enterprise freight brokerages, convert them to paid engagements, and build the go-to-market motion targeting Heads of Logistics, Supply Chain, and Operations
• Partner with the FutureSight product and engineering team to ship V1 and iterate on user feedback, with a focus on TMS and load board integrations, conversational AI quality, and autonomous workflow execution
• Lead the seed raise, supported by FutureSight's network and traction
• Recruit and lead the founding team, and establish the cultural foundation of the company

Co-Founder & CEO – AI Communication Agents, Freight & Logistics

• Set the direction of the venture and lead its execution.
• Refine the ICP, pricing model, and product positioning across the AEC vertical wedge
• Lead pilots with mid-market AEC firms, convert them to paid engagements, and build the go-to-market motion through AEC networks, marketing associations, and industry partnerships
• Partner with the FutureSight product and engineering team to ship V1 and iterate on user feedback, with a focus on compliance extraction, semantic mapping, and SME workflows
• Lead the seed raise, supported by FutureSight's network and traction
• Recruit and lead the founding team, and establish the cultural foundation of the company

Co-Founder & CEO – AI Proposal Intelligence for AEC

• Drive the technical vision, research and engineering execution for the Voice AI platform
• Provide executive technical leadership to a unified research and engineering organization
• Manage and scale a unified Voice AI research and engineering organization distributed across multiple geographies
• Own the entire engineering lifecycle for central, reusable Voice AI models and foundational AI infrastructure
• Define, implement, and track key technical performance metrics to measure engineering success
• Evaluate and integrate cutting-edge Voice AI research and technologies

Director of Voice AI

• Responsible for managing project initiatives of strategic importance to the organization.
• Participate in customer workshops and design call flows using our products using design best practices and awareness of product nuances.
• Work Independently, and with Genesys technical teams and business partners, to design, develop and maintain IVR’s, NLU Intent-based Bots and routing applications for DTMF and speech interactions, Virtual Agents, and Agentic Virtual Agents.
• Experience defining ASR grammars, and tuning process.
• Create accurate development effort estimates in collaboration with the team manager, Professional Services project managers or regional managers.
• Works on significant and unique issues where analysis of situations or data requires an evaluation of broadly defined variables.
• Requires conceptual thinking to understand advanced issues and implications.
• Exercises independent judgment in methods, techniques and evaluation criteria for obtaining results.
• Accountable for results, which may impact their entire function or geography.
• Work with Product owner, Scrum master to drive user story creation and ownership for SS&AI owned epics for IVR, Routing and bots.
• Lead the SS&AI team delivery.
• Present and demonstrate proposed IVR solutions as required.
• Perform knowledge transfer of the delivered solutions at the conclusion of the engagement as necessary.
• Create and execute test scripts for call flow and other logic and leverage existing Genesys tools (logs, reporting) to provide UAT and QA support.
• Communicate within the global community respecting cultural, language and time zone variations.
• Demonstrate flexibility to adjust working hours to match customer and team interactions.
• Work as a team player to the organization.
• Providing feedback to the product organization about issues found in API’s, product, documentation or architectures.
• Work independently to provide customer technical consulting services to help drive the determination of key deliverables, outcomes, code best practices, and deployments.

AI Implementation Principal Consultant

• Engage with clients to understand their needs and provide expert advice on AI solutions.
• Assist in the preparation and delivery of presales presentations and proposals.
• Conduct technical workshops and demonstrations of Genesys AI products.
• Collaborate with clients to design, develop, and deploy AI bots and machine learning solutions.
• Lead project work from inception through to successful delivery.
• Ensure AI solutions are integrated seamlessly with client systems and processes.
• Provide ongoing support and consultation post-deployment to ensure maximum value realization.
• Monitor and optimize deployed AI solutions for performance and effectiveness.
• Stay up to date with the latest developments in AI technology and use cases.
• Gain in-depth knowledge of the entire Genesys Cloud Digital suite.
• Participate in ongoing training and professional development.
• Work as a team player to the organization. Providing feedback to the product organization about issues found in API’s, product, documentation or architecture.

Senior Digital AI Professional Services Consultant

• Define and scale a global AI sales motion that transforms how enterprise AI solutions are positioned, validated, and adopted across industries.
• Connect business value with technical innovation, ensuring organizations realize meaningful outcomes from AI-driven customer experience orchestration.
• Lead a globally distributed organization of AI Sales Specialists and regional leaders, operating in a coordinated “two-in-a-box” model with AI Architects.
• Drive business value articulation, technical validation, and successful customer outcomes.
• Shape how complex opportunities are developed and won.
• Help scale repeatable approaches that move customers from initial concept through prototype, pilot, and full production.
• Engage with diverse teams, customers, and partners worldwide, fostering an inclusive environment.

Vice President, Global AI Sales Specialists

• Set the Digital & AI direction for the Service Line
• Create an Architecture + Urbanismspecific digital & AI strategy in the context of our 3yr-out vision and strategy of the Architecture + Urbanism, and the strategic priorities of Industries & Sectors.
• Define and regularly update “digital must-win” areas by conducting competitor analyses and gap analysis within existing portfolio of tools and digital products and partnerships.
• Identify which Architecture + Urbanism delivery domains and workflows must be redesigned.
• Setup collaboration rhythm with Digital Intelligence, Investment governance, pipeline management approach and prioritization framework, change network, CoPs, etc.
• Set clear objectives for the transformation that link to overall Architecture + Urbanism performance metrics.
• Own the Opportunity Portfolio
• Collect and pro-actively source digital opportunities and use cases within the organization, in close collaboration with peers in other Service Lines and Industries.
• Kick-start and actively participate in AI studios around the most promising opportunities, to quickly validate and potentially prototype, ideally in real client settings.
• Work closely together with Digital Intelligence counterparts to make buy/build/partner decisions, as well as start/continue/stop decisions, following pre-set guidelines.
• Actively stop or kill initiatives that do not demonstrate clear value, adoption potential, or strategic fit.
• Participate regularly in client conversations to better understand client needs.
• Act as primary interface and product sponsor to product managers, e.g., help get funding, set requirements, mobilize business SME involvement, anything needed to deliver at pace.
• Rewire Service Delivery workflows
• Redesign end-to-end Architecture + Urbanism delivery workflows to embed digital and AI where they materially improve outcomes.
• Work with Service Line leadership to support adjustments to new ways of working.
• Embed Digital & AI in our capabilities and drive adoption
• Build a local network of digital & AI champions (change agents and catalysts) within each Service Area Group.
• Strengthen foundational digital skills and AI usage within the organization (e.g., Drive Citizen Development participation, measure and steer on AI usage, make part of SPO)
• Setup adoption campaigns around new tooling / digital products, and ways of working, incl. training programs and updated global procedures.
• Strengthen data foundations and other boundary conditions
• Turn global data strategy into an actionable plan within the service line, with clear focus around the priority areas (digital must-wins).
• Create knowledge and data libraries around discipline areas, managed within Communities of Practice.
• Setup data governance (who collects, who structures and maintains) and measure adherence and progress.
• Define any other pre-requisites for digital innovation and bake into transformation plan.
• Own the Architecture + Urbanism Digital and AI innovation backlog and roadmap, in partnership with Digital Intelligence, ensuring alignment to strategic priorities and measurable value delivery.
• Drive investment prioritisation and portfolio transparency within the Innovation governance framework, enabling clear decision-making and optimal allocation of resources.
• Champion digital adoption across the Architecture + Urbanism workforce and project delivery, working closely with Services leadership to embed tools, behaviours, and ways of working that maximise impact.

Digital & AI Transformation Director – Architecture, Urbanism

• Own execution of the AI Review Framework
• Ensure governance processes are consistent, efficient, and audit-ready
• Execute AI governance activities through the AIS / Security Governance Team
• Perform AI risk classification (low, mid, high)
• Assess: Business impact, Customer and regulatory risk, Data sensitivity
• Prepare governance recommendations for CIO, CLO, and AIS Committee
• Own vendor AI governance execution, including: AI usage detection across vendor portfolio, FactSheet collection and review
• Ensure vendor AI is properly routed through the AIS Program review process
• Partner with Vendor Management on third-party risk alignment
• Coordinate twice-annual AI system validations
• Track: Model updates, Control gaps and remediation, Ensure FactSheet updates trigger re-reviews
• Work with member carriers to guide teams through AI governance requirements
• Ensure consistent application of policies and standards
• Support adoption of shared AI governance practices
• Maintain AI inventory, Governance documentation and decision logs
• Prepare materials for AIS Committee, Leadership reporting
• Partner with AI / Data Science teams, Legal and Compliance, Vendor Management, and coordinate with Cyber / Privacy teams as needed

Senior Manager, AI Risk & Governance

• 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

• Lead Enterprise AI Literacy Learning
• Governance for Learning Collaboration Team Tools & Processes
• Identify & Pilot Innovative AI Learning Tools

Director, Enterprise AI Learning, Governance, Innovation

• 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.

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