Search, indexing and query as a product surface: End-to-end ownership of how customers express and satisfy a query on Couchbase — SQL++ query, global secondary indexes, full-text search, and vector and hybrid search. The roadmap in your area, the PRFAQs and PRDs, the launch, the adoption, and the iteration after launch.
Retrieval for AI applications: Make Couchbase the retrieval layer that RAG applications and agents actually use — hybrid search relevance, metadata filtering, recall and freshness, and cost per query. Work with the wider AI portfolio so retrieval composes with the rest of the platform rather than sitting beside it.
Developer experience for query and indexing: How a developer writes a query, gets an index recommendation, debugs a slow plan, and understands what a query costs. Reduce the number of things a developer has to know before their first query is fast.
Performance, cost and benchmark credibility: Own the performance story for your area. Reproducible benchmarks the field can stand behind, a defensible cost and TCO narrative against MongoDB, Elastic, Postgres and pgvector, and dedicated vector stores, and a clear point of view on where Couchbase wins and where it does not.
Working backwards from the customer: Start with the customer and work backwards. Write the PRFAQ before any code is written. Validate with real, named enterprise customers. Make clear tradeoff calls about what to build and what to defer based on what the enterprise ICP universally needs — not features chasing competitors or one-off requests outside the ICP.
Engineering partnership: Work shoulder-to-shoulder with the query, indexing and search engineering teams. Earn their trust by being technically credible, decisive on scope, and clear on the why. Own the PRD as a living document, not a one-time artifact. Hold the bar on quality, scope, and timing through to launch.
Customer and design partner engagement: Run design partner programs for the capabilities you own. Bring real customer voice into roadmap decisions and back to the broader team. Help build a pipeline of named reference customers willing to talk publicly about what they have shipped.
Cross-portfolio collaboration: Coordinate across Core Database, Capella, Analytics, Mobile and Edge, and the AI Specialist team so the capabilities you own compose cleanly with the rest of the platform. Bring a build-vs-partner point of view to your area.
Sales and GTM partnership: Equip sales, sales engineering, PMM, and partner GTM with what they need to win on search, indexing and query — positioning, demos, competitive context, benchmark data, customer proof points. Be the product owner in deals where the technical depth matters.
External voice: Contribute as the product owner in customer briefings, webinars, blog posts, documentation, and enablement content for the capabilities you own. Support analyst engagements and keynote content led by the Principal PM, PMM, and AR.
AI-driven PM practice: Use AI deeply and visibly in your own product management work — research, PRFAQ drafting, customer synthesis, competitive analysis, benchmark analysis, engineering collaboration. Adopt and contribute to the team’s AI-driven PM and AI-DLC (AI-driven development lifecycle) practices in day-to-day execution.
Raising the bar: Share what works. Contribute to PRFAQ and PRD standards, interview loops, and onboarding. Mentor associate and early-career PMs as the team grows.
PRFAQs and PRDs for the capabilities you own, validated with named enterprise customers before engineering starts.
Shipped capabilities across query, indexing and search with measurable adoption and at least one named reference customer per major launch.
A published, reproducible performance and cost position for your area that sales and engineering both stand behind.
Clear, defensible tradeoff decisions visible to engineering, sales, and GTM. The team knows what is in, what is out, and why.
Sales and GTM enablement that the field actually uses — measured by pipeline influence and win-rate signals, not enablement-decks-produced.
Contributions to the broader platform narrative — customer-facing content, blog posts, and documentation in partnership with the AI Specialist team, PMM, and AR.
Visible AI-driven PM practice — concrete examples of AI-DLC in your daily work that the rest of the team can learn from.