Agentic AI — AI-Native Senior Product Manager

You will own the product for a fully custom agentic platform being built from the ground up, and will need to think far beyond the chat experience You don't need to be an engineer, but you need to reason fluently about how architectural choices affect product decisions You will own multi-agent workflow design: defining what jobs agents perform, how tasks are decomposed across agents, and where human-in-the-loop checkpoints belong You will need to understand a wide ranging set of domains, expanding across multiple products serving different customer segments — you will think across abstraction and customization, knowing what to generalize and what must be tailored per product or vertical As the Senior Product Manager you will own the product for a fully custom agentic platform being built from the ground up, and will need to think far beyond the chat experience You don't need to be an engineer, but you need to reason fluently about how architectural choices affect product decisions You will own multi-agent workflow design: defining what jobs agents perform, how tasks are decomposed across agents, and where human-in-the-loop checkpoints belong You will need to understand a wide ranging set of domains, expanding across multiple products serving different customer segments — you will think across abstraction and customization, knowing what to generalize and what must be tailored per product or vertical.

Use AI tools as core infrastructure in your daily work, not as novelties, but as force multipliers for research, analysis, communication, and decision-making, including:
Compress discovery and validation cycles by using AI to synthesize customer feedback, analyze competitive landscapes, and generate first-draft artifacts (PRDs, specs, mockups) that you then refine with product judgment Architect your own analysis pipelines: use AI to query and synthesize large datasets, extract patterns from user interviews, and surface insights that would otherwise require weeks of manual effort Continuously evolve your AI toolkit and share effective patterns with the broader product organization Prototype and validate product concepts rapidly.

Arrive at planning discussions with working proofs-of-concept, not just slide decks Maintain deep fluency in the AI product landscape: what competitors are building, what customers are adopting, and where the technology is heading Own and communicate the strategic roadmap for your assigned product area. Identify where AI creates transformative value versus incremental improvement, and prioritize accordingly Think architecturally: build capabilities that solve multiple problems and expand the product's surface area, rather than addressing isolated requests Translate quantified customer signals (revenue impact, churn risk, deal blockers) into product decisions that go beyond feature requests Lead the full product lifecycle: discovery, definition, development, evaluation, launch, and iteration.

Own execution with engineering teams. Partner with GTM teams to ensure product capabilities are positioned, launched, and adopted Ship iteratively: establish feedback loops with real users early and often, and use data to inform the next cycle Other Duties as assigned.

• Bachelor's degree or equivalent work experience
• 5+ years of product management experience in a software/SaaS environment
• Demonstrated, meaningful use of AI tools in your own PM workflow. You should be able to speak concretely to how AI has changed the way you work, what it's replaced, and where you've found its limits
• Experience building or shipping product capabilities that incorporate AI/ML, with at least one production deployment preferred
• Experience working with engineering teams on AI/ML systems (model integration, context engineering, evaluation pipelines, data quality)

• Working understanding of foundation models, their capabilities, limitations, and appropriate use cases
• Familiarity with AI product patterns: RAG, agentic workflows, embeddings, fine-tuning, and evaluation frameworks
• Understanding of APIs, cloud infrastructure, data pipelines, and modern development practices
• Comfort using AI-assisted…