The opportunity
Today, everyone from PMs to Sales to SREs uses AI to query their business data - but every answer is a one-off with no governance, no consistency, and no visibility for data teams. We're building the system that fixes this: a context layer that learns from existing data tools…
What you'll do
Drive the product vision and roadmap spanning the Data agent experience, the: semantic/context layer, governance console, chat experience and analysis surfaces (dashboards, notebooks, sheets)
Own the end-to-end product lifecycle from discovery to launch, working with a: cross-functional team of engineers, designers and other PMs
Deeply understand the needs of two key personas: data teams (who govern and curate) and data consumers (PMs, engineers, SREs, executives who ask questions)
Design the context and governance layer that makes AI-powered analytics: trustworthy - including auto-generation from existing BI tools, eval frameworks, confidence scoring, and self-improvement loops
Define how observability data and business data come together to serve unique use cases
Engage directly with early customers and internal dogfooding users to iterate: on accuracy, usability, and trust
What they're looking for
- + years of experience in B2B SaaS Product Management, with at least some of: it spent on data-intensive or analytics products
- You have domain knowledge of business intelligence, data visualization,: semantic layers, data warehouses and the modern data stack.
- Strong analytical skills: you can write SQL, interpret complex data, and use data to drive product decisions
- Experience with AI/LLM-powered products is a strong plus: you understand prompt engineering, evals, and the unique UX challenges of non-deterministic systems
- You are AI-pilled. You live in Claude Code or Cursor, have built unique AI: workflows for yourself, hack around with new tools. etc
- You have a strong sense of ownership with an entrepreneurial mindset: this is a 0-to-1 product that requires someone comfortable with ambiguity and speed
- Sharp communication skills with the ability to interact with technical stakeholders and executives alike.
- Bachelor's Degree in Engineering, Computer Science, Data Science, or equivalent experience is a plus
