Job Title

Responsibilities may include the following and other duties may be assigned.Plans, directs and implements all aspects of the company's design and development of new medical device products or software systems.May develop, evaluate, implement and maintain technical quality assurance and control systems or reliability systems and standards pertaining to materials, techniques, or company products.Oversees the investigation and evaluation of existing technologies.Guides the conceptualization of new methodologies, materials, machines, processes or products.Directs the development of new concepts from initial design to market release.Manages feasibility studies of the design to determine if capable of functioning as intended.Monitors documentation maintenance throughout all phases of research and development.Organizes the coordination of activities with outside suppliers and consultants to ensure timely delivery.Selects, develops and evaluates personnel to ensure the efficient operation of the function.Strategic Vision & GovernanceArchitect of Transformation: Translate the Chief AI Officer’s global vision into a robust regional technical strategy, ensuring the AI COE remains at the vanguard of the Enterprise AI roadmap.Global Engineering and Program Management: Interface with all 14 operating units across global business structure to support the AI COE enterprise AI enablement strategy. Guide the team to produce high level quality and measurable outcomes that are then embedded into the operating unit processes, products, and solutions.Governance & Strategic Alignment: Represent the site in critical global governance forums (QMR, Leadership Connects). Ensure absolute compliance with the AI COE operating model and global KPIs.Stakeholder Synergy: Interface directly with global OU R&D leadership to support on-time, in-budget execution. Maintain high-level relationships with internal and external partners, including IT and Hyperautomation programs, to ensure total alignment with the enterprise roadmap.Ecosystem Orchestration: Champion technical brand within the regional AI ecosystem, engaging with elite academic institutions, startups, and industry bodies to influence the trajectory of innovation.Program Leadership & Infrastructure ManagementProgram Leadership: Drive cross functional alignment, disciplined delivery, and measurable business impact for AI application programs. Lead communication to global operating units and synthesized strategic communications to the enterprise AI COE.Strategic Execution Leadership: Oversee the end-to-end development and deployment of AI solutions. Manage the budget, delivery timelines, and critical KPIs for the AI COE team and global programs.Infrastructure Readiness: Own the readiness and optimization of AI infrastructure, including specialized labs and high-scale compute resources required for advanced model training.Resource & Vendor Orchestration: Coordinate complex vendor engagements and External Service Provider (ESP) resources to augment team capacity and technical depth.Full-Spectrum Delivery: Drive rigorous execution across the complete data lifecycle: Data Science, Data Engineering, and Annotation ServicesEngineering Excellence & Technical OversightTechnical Stewardship: Provide executive oversight for the architectural integrity of integrated software algorithms, ensuring AI solutions are robust, scalable, and ethically sound across structured and unstructured environments.Algorithmic Mastery: Accountable for the high-fidelity performance of predictive, prescriptive, and descriptive algorithms. Ensure that technical specifications are translated into production grade code with high precision.Innovation Synthesis: Lead the adaptation of cutting-edge ML into specialized domains such as Robotics, Augmented Reality (AR), and Interactive Systems, bridging the gap between theoretical research and product grade engineering.Data Strategy & Sovereignty: Partner with the Global Data Office to define sophisticated data strategies, ensuring pipelines and modeling environments are optimized for next-generation AI training.Talent, Capability & Culture BuildingEnterprise Capability Building: Lead AI upskilling initiatives using platforms like Coursera, Worker, and Degreed to maintain a state-of-the-art technical workforce.Knowledge Orchestration: Establish Communities of Practice and structured knowledge sharing sessions to democratize AI expertise across the enterprise.Talent Management: Oversee the full talent lifecycle, including onboarding, performance coaching, and career development. Align resource planning with project pipelines and high-priority OU needs.Culture of Excellence: Build a distinctive /"Culture of Innovation/" at the site that balances rigorous engineering discipline with creative research freedom.Differentiating Leadership FactorsStrategic Acumen: The ability to navigate a complex, matrixed global organization and influence executive-level stakeholders on the long-term ROI of AI investments.Engineering Sophistication: A /"leader-as-expert/" profile capable of conducting deep technical due diligence and architectural reviews.Operational Autonomy: Empowered to make high-stakes decisions that impact financial performance, employee engagement, and the global image of AI.Required Knowledge and Experience:Bachelor’s degree in Electronics & Communication, Computer Engineering, AI/Data Science, or a related technical field20+ years of relevant professional experience with a focus on technical leadershipMinimum of 10+ years of managerial experienceDeep expertise in modern programming ecosystems, large-scale computing frameworks, and the full lifecycle of AI productizationExperience interfacing with global business teams to drive business results