• Setting the long-term technical vision for distributed AI communication systems • Conducting original research and prototyping next-generation networking solutions • Driving hardware-software co-optimization with various technologies • Investigating fundamental bottlenecks in communication runtimes for large-scale AI workloads • Integrating networking capabilities into AI serving stacks • Publishing findings and representing NVIDIA in industry forums and standards bodies • Mentoring senior engineers across the organization

• You'll operate at the crossroads of AI product strategy, (pre) sales and customer success. • Work hand-in-hand with Product Managers and Engineers, and go-to-market (GTM) teams, to define, develop, and launch conversational AI agents that power large volumes of live customer interactions. • The role blends strategic thinking with hands-on agent design, requiring fluency in both business context and technical execution. • Serve as a strategic partner to customers, supporting the evolution, execution, and adoption of concrete AI initiatives. • Convert business requirements into well-designed, high-performing AI agents. • Lead delivery across multiple concurrent complex agentic projects that receive maximum visibility both from customer side as well as from the NiCE perspective. • Bridge the gap between technical teams and business stakeholders throughout the entire development lifecycle. • Shape agent behavior through conversational design, product intuition, and performance data. • Surface data-driven action items and iterations that sharpen both customer outcomes and internal decision-making.

• You'll operate at the crossroads of AI product strategy, (pre) sales and customer success. • Work hand-in-hand with Product Managers and Engineers, and go-to-market (GTM) teams, to define, develop, and launch conversational AI agents that power large volumes of live customer interactions. • The role blends strategic thinking with hands-on agent design, requiring fluency in both business context and technical execution. • Serve as a strategic partner to customers, supporting the evolution, execution, and adoption of concrete AI initiatives. • Convert business requirements into well-designed, high-performing AI agents. • Lead delivery across multiple concurrent complex agentic projects that receive maximum visibility both from customer side as well as from the NiCE perspective. • Bridge the gap between technical teams and business stakeholders throughout the entire development lifecycle. • Shape agent behavior through conversational design, product intuition, and performance data. • Surface data-driven action items and iterations that sharpen both customer outcomes and internal decision-making.

Lead the development lifecycle for AI/ML models, manage a team of Data Scientists, identify improvement opportunities, and provide stakeholder updates to ensure alignment with business goals and project timelines.