Artificial Intelligence

• Architect and design end-to-end AI/ML solutions for the MediaOS platform
• Define and implement scalable ML pipelines, including data ingestion, feature engineering, model training, deployment, and monitoring
• Lead the design of cloud-native, distributed AI systems leveraging modern frameworks and high-performance computing environments
• Partner with product, data engineering, and platform teams to translate business requirements into robust AI-driven solutions
• Establish and enforce MLOps best practices, including CI/CD, model versioning, observability, governance, and lifecycle management
• Evaluate and integrate emerging AI technologies, including Generative AI, LLMs, and NLP applications where applicable
• Drive data strategy alignment, ensuring high-quality, well-governed datasets to support model development and scalability
• Mentor and guide engineers and data scientists, fostering a culture of innovation, collaboration, and technical excellence
• Architect secure AI platforms, including authentication and authorization models (e.g., RBAC, ABAC)

AI/ML Architect, MediaOS Platform

• Maintain strong awareness of the rapidly evolving AI ecosystem
• Translate new AI capabilities into practical engineering patterns
• Accelerate adoption of the enterprise AI platform across engineering teams
• Ensure experimentation leads to reusable capabilities rather than isolated prototypes
• Provide a clear feedback loop to the AI Platform organization on emerging needs
• Continuously evaluate emerging AI technologies and techniques that can meaningfully improve enterprise AI systems
• Develop prototypes and reference implementations that validate new AI approaches
• Translate experimentation into practical assets that accelerate the development of production AI systems across the organization
• Help engineering teams adopt AI capabilities effectively

VP, AI Innovation – Enablement

• Champion Agile principles and practices across AI and data-focused teams, driving adoption and continuous improvement
• Coach product owners, engineers, and business stakeholders on Agile frameworks such as Scrum, Kanban, or SAFe
• Facilitate core Agile ceremonies (sprint planning, stand-ups, reviews, retrospectives) to ensure effective team execution
• Foster a culture of transparency, collaboration, and iterative delivery across cross-functional teams
• Partner with technical teams (data science, ML engineering) and business leaders to translate AI use cases into actionable backlogs and sprint goals
• Guide teams in delivering AI/ML solutions iteratively, accounting for experimentation, model training, and validation cycles
• Align delivery plans with business objectives, ensuring AI initiatives provide measurable value
• Support prioritization of work based on business impact, technical dependencies, and data readiness
• Enable collaboration across diverse teams, including data scientists, engineers, product managers, and domain experts
• Remove impediments and escalate risks impacting delivery timelines or outcomes
• Act as a liaison between technical and non-technical stakeholders to ensure shared understanding
• Define and track Agile and AI-specific performance metrics (e.g., velocity, cycle time, model performance indicators)
• Ensure AI delivery adheres to governance, compliance, and ethical standards (e.g., bias, data privacy)
• Facilitate retrospectives and apply learnings to improve delivery effectiveness and team maturity
• Promote data-driven decision-making and experimentation
• Support enterprise Agile transformation efforts, particularly within AI and digital initiatives
• Influence leaders and stakeholders to adopt Agile ways of working and AI-enabled delivery models
• Drive mindset shifts toward iterative development, experimentation, and continuous learning

AI Agilist

• 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

• Own the day to day operational enablement of Microsoft 365 Copilot across the enterprise
• Configure, test, enable, and maintain Copilot features, settings, and options within the Microsoft ecosystem
• Ensure Copilot remains functional, secure, and usable as Microsoft introduces updates and new capabilities
• Partner with IT security, infrastructure, applications, and service teams to align AI enablement with operational standards
• Translate AI capabilities into practical, repeatable use cases that improve employee productivity
• Work directly with BioCryst business and functional departments to support AI implementation within their systems and workflows
• Help departments identify opportunities where AI can improve efficiency, accuracy, or decision‑making
• Own IT training and enablement for new hires, system changes, and technology rollouts
• Develop and maintain clear, accurate IT documentation and self‑service resources

Associate Director – AI Enablement, IT Training

• lead the KCS Center of Excellence (COE) across the Cisco TAC organization
• be the primary architect of the global knowledge strategy
• mentor, manage, and provide strategic direction to a team of KM Leaders and KCS Knowledge Leads
• partner with Technology Group Owners, Technical Strategy Leaders, Engineering teams to integrate KCS practices with AI-driven support tools
• serve as the main liaison between Operations teams, Technology Group Owners, Product Leaders, and IT
• establish enterprise-wide governance for knowledge quality and accessibility
• drive the evolution of a 'knowledge-first' culture
• leverage industry benchmarking and internal data to iterate on processes, tools, and enablement strategies

Lead, Knowledge & AI Support Automation Management

• 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

• Develop and extend C++ and Python simulators that model system-level network and compute traffic for agentic LLM workloads in datacenter environments
• Characterize real-world LLM serving workloads and distill them into representative simulator inputs
• Run simulations at scale and apply statistical techniques to post-process and interpret results
• Identify performance bottlenecks and translate findings into concrete architectural recommendations
• Collaborate with hardware, software, and research teams to influence the design of future AI systems

Systems Performance Engineer – Agentic AI Workloads

• Drive end-to-end delivery of production AI platforms
• Lead solution architecture, orchestrate model pipelines, and design multi-agent workflows
• Create reusable SDKs and frameworks
• Collaborate across product, engineering, security, and governance teams
• Ensure AI systems are scalable, observable, cost-efficient, and compliant
• Define design patterns and optimize operational pipelines
• Enable internal reuse of proven solutions
• Own the full lifecycle from architecting secure, compliant solutions to deploying and scaling them in production
• Work with Azure OpenAI, Azure AI Search, multi-agent orchestration, and API integrations for EHR, CRM, and member portals

Senior Artificial Intelligence Engineer

• 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

• 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

• Develop and own the enterprise AI enablement strategy, including training programs, change management frameworks, and adoption roadmaps
• Design and deliver hands-on workshops, learning paths, and onboarding programs that upskill employees at all levels on AI tools and workflows
• Serve as the primary connector between technical AI teams and business units, translating capabilities into practical, day-to-day use cases
• Build and manage an internal AI community of practice to share learnings, best practices, and success stories
• Define and track adoption KPIs — measuring utilization, productivity impact, and ROI across AI initiatives
• Partner with HR, L&D, and Communications to embed AI fluency into the employee experience
• Develop governance guardrails and responsible AI usage guidelines for the broader workforce
• Stay current on emerging AI tools, trends, and vendors, and bring relevant insights back to the business

AI Adoption & Enablement Lead

• 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

• Translate business needs into technical systems solutions and architectural roadmaps
• Work on problems of diverse scope and complexity
• Expert in 24/7 operations with high performing systems
• Spearhead research, evaluation and deployment of AI and GenAI capabilities
• Bridge traditional IT Operations with emerging AI technologies
• Collaborate with Infrastructure and Cloud Operations teams to pilot and integrate AI/GenAI features
• Lead research and evaluation of AI and GenAI tools for Infrastructure Operations
• Develop and lead the strategic roadmap for AI adoption in Infrastructure Operations
• Identify automation opportunities and implement AI-enhanced runbooks

Infrastructure Operations Lead – Cloud and AI GenAI Enablement

• Own delivery, performance, and risk outcomes for a large, complex Claims Applied AI portfolio spanning multiple teams, domains, and value streams
• Drive measurable business value across the end-to-end claims journey by developing, testing, deploying, and scaling Predictive, Generative, and Agentic AI solutions
• Be the senior business partner for Claims leaders
• Build deep partnerships within portfolio and value stream frameworks
• Lead and develop senior leaders and teams
• Provide portfolio-level technical direction and oversight
• Ensure disciplined architecture and delivery trade-offs across quality, grounding, latency, cost, scalability, and regulatory risk
• Establish and enforce evaluation, monitoring, and production readiness across solution types
• Set governance expectations for unstructured data and retrieval across Claims
• Accountable for AI governance and compliance-by-design across the Claims portfolio
• Influence technology integration and platform strategy
• Champion reuse and scalability by partnering with AI platform owners and peers
• Provide thought leadership and change leadership
• Oversee portfolio planning, dependencies, resourcing, and financial stewardship

AVP Applied AI, Claims

• Supporting research and documentation efforts, including building internal repositories or reference materials.
• Assisting with SharePoint site development, content organization, and design updates.
• Performing data cleaning, analysis, and visualization using Excel and other dashboards.
• Participating in team‑specific technical tasks such as Python scripting, cybersecurity analysis, or special project support.
• Preparing and delivering concise presentations summarizing project work and outcomes.
• Applying structured problem‑solving approaches such as the CORE method to improve processes or address challenges.

Intern – Digital Solutions & AI

• Act as an advisor to senior leadership in developing a large cross functional team to identify and execute complex artificial intelligence initiatives that span a large line of business
• Provide consultation to more experienced leaders in order to recommend solutions which solve business challenges
• Lead the strategy and resolution of highly complex challenges ensuring the solution delivers the intended benefits
• Leverage Artificial Intelligence expertise to evaluate technological readiness, data availability, and resources required to execute the proposed solutions
• Provide direction on key issues which may arise during development or implementation
• Cultivate relationships with clients to identify and develop a pipeline of future Artificial Intelligence opportunities which align with the strategic priorities of the business
• Collaborate and consult with peers, colleagues, and managers to resolve issues and achieve goals

Senior Lead Artificial Intelligence Consultant

• Define and own the AI product strategy, outcomes, and end‑state vision, aligning WIM AI initiatives to enterprise priorities and measurable business value.
• Lead end‑to‑end product management for complex, enterprise‑grade AI platforms, solutions, and capabilities, ensuring scalability, governance, and operational readiness.
• Partner closely with the WIM Head of AI & Digital Asset Platforms to shape AI roadmaps, investment decisions, prioritization, and product tradeoffs.
• Translate business problems into prioritized AI use cases, value cases, and delivery plans across advisor, client, and operations domains.
• Drive cross‑product AI portfolio management, identifying dependencies, synergies, and risks across platforms, workflows, and distribution channels.
• Guide long‑term AI solution delivery, accounting for regulatory requirements, responsible AI principles, data dependencies, and enterprise technology constraints.
• Articulate AI product vision and roadmap; define scope; prioritize backlogs; and support platform evolution, model deployment, and workflow integration.
• Own key business, adoption, operational, and risk metrics, embedding governance, controls, and compliance requirements throughout the AI product lifecycle.
• Engage and align cross‑functional teams and external partners, including Product Owners, Engineering, Data, Risk, Compliance, Legal, Operations, and vendors.
• Serve as a trusted advisor to senior leadership, translating complex AI, regulatory, and market considerations into clear product direction and execution plans.

Executive Director – Artificial Intelligence, AI

• Own delivery of large and/or complex ML, DL, and Generative AI systems
• Design, implement, and evaluate AI systems for production
• Apply prescriptive analytics techniques to business problems
• Lead development and testing of ML algorithms
• Stay updated with advancements in AI/ML methods
• Benchmark against existing ML methods
• Develop prototypes and proof-of-concept implementations
• Lead consultation sessions with business partners
• Drive continuous improvement through novel techniques
• Identify actionable insights and communicate results

See all jobs on JobTailor