Product Strategy & Vision (AI/ML & Scale): Define and evangelize the product vision, strategy, and roadmap for our AI/ML platform, data pipelines, and scalable application infrastructure, aligning with overall company objectives. Identify market opportunities, customer needs, and technical trends to drive innovation and competitive advantage in the AI/ML and large-scale data domain. Translate complex technical challenges and opportunities into clear, actionable product requirements and specifications. Product Development & Execution Leadership: Oversee the entire product lifecycle from ideation and discovery through development, launch, and post-launch iteration for critical AI/ML and data products. Work intimately with engineering, data science, and operations teams to ensure seamless execution and delivery of high-quality, performant, and scalable solutions. Champion best practices for productionizing applications at scale and ensuring our systems can handle huge volumes of data efficiently and reliably. Define KPIs and metrics for product success, monitoring performance and iterating based on data-driven insights. People Management & Team Leadership: Lead, mentor, coach, and grow a team of Technical Product Managers, fostering a culture of innovation, accountability, and continuous improvement. Provide clear direction, set performance goals, conduct regular reviews, and support the professional development and career growth of your team members. Act as a leader and role model, promoting collaboration, open communication, and a positive team environment. Technical Expertise & Hands-On Contribution: Possess a deep understanding of the end-to-end ML lifecycle (MLOps), from data ingestion and model training to deployment, monitoring, and continuous improvement. Demonstrate strong proficiency in Google Cloud Platform (GCP) services, including but not limited to, compute, storage, networking, data processing (e.g., BigQuery, Dataflow, Dataproc), and AI/ML services (e.g., Vertex AI, Cloud AI Platform). Maintain a strong hands-on expertise level in Python programming, capable of contributing to prototypes, proof-of-concepts, data analysis, or technical investigations as needed. Extensive practical experience with leading AI frameworks and libraries, including Hugging Face for natural language processing and transformer models. Proven experience with LangGraph (or similar sophisticated agentic frameworks like LangChain, LlamaIndex), understanding their architecture and application in building intelligent, multi-step AI systems. Solid understanding of agentic frameworks, their design patterns, and how to productionize complex AI agents. Excellent exposure to GitHub and modern coding practices, including version control, pull requests, code reviews, CI/CD pipelines, and writing clean, maintainable code. Cross-functional Collaboration & Stakeholder Management: Collaborate effectively with diverse stakeholders across engineering, data science, design, sales, marketing, and executive leadership to gather requirements, communicate progress, and align strategies. Act as a bridge between technical teams and business stakeholders, translating complex technical concepts into understandable business implications and vice-versa.