AI/Analytics Product Manager

Required Skills Product Management * Experience managing AI, Analytics, or Data products throughout the product lifecycle. * Strong product strategy, roadmap planning, prioritization, stakeholder management, and execution skills. * Experience translating business requirements into product features and technical capabilities. * Strong understanding of customer-centric product development and outcome-based delivery. * Experience defining KPIs, OKRs, success metrics, and product analytics. Agile Delivery * Hands-on experience with Agile/Scrum methodologies. * Experience managing product backlogs, user stories, sprint planning, release planning, and incremental product delivery. * Strong collaboration across cross-functional engineering, architecture, data, and business teams. Agentic AI & Generative AI * Experience designing, building, and managing autonomous AI agents, including single-agent and multi-agent systems. * Hands-on experience with agentic frameworks such as LangGraph or similar orchestration frameworks. * Knowledge of LLM orchestration, tool calling, function calling, planning, reasoning, workflow decomposition, and AI agent lifecycle management. * Experience building AI solutions using Retrieval-Augmented Generation (RAG) architectures. * Knowledge of vector databases, embeddings, semantic search, hybrid retrieval, prompt engineering, grounding strategies, and context optimization. * Experience implementing AI-powered automation, self-healing workflows, anomaly detection, automated root-cause analysis, and intelligent remediation capabilities. * Understanding of Responsible AI, AI governance, model evaluation, observability, and monitoring. Data Science & Analytics * Strong understanding of Data Science lifecycle, statistical analysis, machine learning concepts, predictive analytics, and experimentation. * Experience working with structured and unstructured data to derive actionable business insights. * Knowledge of feature engineering, model evaluation, model performance monitoring, and AI/ML solution lifecycle. * Experience partnering with Data Scientists to operationalize AI and machine learning models into production. * Strong analytical skills with expertise in SQL, data visualization, KPI development, and business intelligence. * Experience leveraging analytics to drive product decisions and measure business impact. Data & Cloud Technologies * Experience with BigQuery, SQL, cloud-native analytics platforms, and modern data architectures. * Understanding of data pipelines, data engineering concepts, APIs, event-driven architectures, and data governance. * Experience working on Google Cloud Platform (GCP) is preferred. * Familiarity with MLOps, CI/CD pipelines, containerization (Docker, Kubernetes), and AI deployment best practices. Leadership Expectations * Strong strategic thinking with the ability to balance long-term vision and execution. * Excellent communication and stakeholder management skills across business and technology organizations. * Demonstrated ability to lead cross-functional teams without direct authority. * Passion for innovation, continuous learning, and delivering measurable business outcomes through AI and analytics. * Hands-on mindset with the ability to work closely with engineering and data science teams to shape solution architecture, validate technical approaches, and drive successful product delivery.