Staff, Product Manager - AI/ML PLatform - Enterprise AI

7+ years in product management at a fast-paced technology company. 3+ years focused on AI/ML initiatives, ideally building platform or framework products. Deep understanding of NLP, LLMs, and AI platform architecture. Strong technical background with experience in AI/ML model lifecycle management. Experience with enterprise AI platforms, model deployment, and MLOps workflows. Deep knowledge of API design, SDK development, and developer platform products. Experience building platform-wide requirements including RBAC, security, and compliance. Proficiency with SQL and ability to extract, analyze, and interpret data independently. Bachelor's degree in Computer Science, Engineering, or equivalent experience. Experience with AI/ML architecture, AI gateway, and agentic AI systems. Experience with multi-agent systems, agentic AI platforms, or AI orchestration. Knowledge of enterprise AI governance, security, and compliance requirements. Experience with cloud services (AWS, GCP, Azure etc.) and ML frameworks. Understanding of conversational AI, RAG systems, and knowledge retrieval. Knowledge of enterprise UI/UX frameworks and component libraries. Background in building developer tools or no/low-code platforms. Experience with A/B testing methodologies and experimental design. Background in building AI platforms for enterprise customers or internal teams.

Own the strategy and roadmap of platform capabilities. Define requirements for the Agent platform, workflow designer, multi-agent architecture, and enterprise capabilities. Maintain documentation for framework APIs, integrations, and best practices. Define and lead technical requirements for model development, training pipelines, and AI reasoning capabilities. Understand internal team and external customer needs for AI agents. Design no/low-code experiences for subject matter experts. Lead the development of cutting-edge AI capabilities. Enable teams to build sophisticated AI agents and evangelize platform capabilities. Deliver measurable improvements in AI response quality, model performance, and platform reliability.