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Senior Product Manager, Search, Indexing and Query

Couchbase | Product Organisation | Bangalore, India | Reports to VP of AI Product Management

About the Role

Couchbase is building the operational data platform for AI. Search, indexing and query are the core of it — how data is found, filtered, ranked and returned is what determines whether an application, or an agent, can actually use the data underneath. We are hiring a Senior Product Manager to own that surface area across Capella and Couchbase Enterprise: the SQL++ query experience, secondary indexing, full-text search, and vector and hybrid search.

This is a hands-on individual contributor role for someone who wants to do the work at the Senior level — write the PRFAQ, sit with the customer, push the tradeoff, ship the capability, and own the outcome after launch. Reporting to the VP of AI Product Management, you will partner closely with the query, indexing and search engineering teams, with sales and GTM, and with the broader AI organization.

You do not need to have shipped a query engine or a search product before. We are hiring for the underlying capability, not the resume line — see “Who This Role Is Open To” below.

What You Will Own

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.

What You Will Deliver

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.

Must Have

Seven or more years in product management, with at least three on a technical platform — database, data infrastructure, search, analytics, developer tools, cloud infrastructure, or AI infrastructure.

Systems depth. You can reason about latency, throughput, recall, index structures, query plans, memory and storage tradeoffs, and cost per operation. Given a benchmark or a slow query, you know what to ask next.

Customer obsession and working-backwards rigor: You start with the customer and work backwards. You write PRFAQs before code. You can tell which feature requests reflect universal ICP needs and which are noise, and you make the call clearly.

Engineering credibility: Engineers want to work with you. You hold your own on architecture, are decisive on scope, and own the why behind every tradeoff.

Cross-functional trust: Sales trusts your roadmap. GTM trusts your enablement. Marketing trusts your narrative. You build durable working relationships outside your own team.

AI-driven PM practice: You already use AI in your own PM work — research, PRFAQ drafting, customer synthesis, competitive analysis — and you can point to concrete examples.

Frontier-model experience: Hands-on experience building with frontier AI models — APIs, code-generation tools, MCP, agent frameworks, and modern developer ecosystems. Familiarity with Anthropic’s Claude stack is strongly preferred.

Strong written communication. Your PRFAQs and PRDs are the artifact the team aligns on, not a chore that follows the work.

A shipping record — products and features you have personally taken from PRFAQ to launch to adoption.

Ability to work effectively with a distributed organization across India and US time zones.

Nice to Have

Direct experience with query engines, query optimization, secondary indexing, full-text search, vector search, or retrieval and ranking systems.

Working familiarity with SQL and SQL-like query languages, Lucene-family search stacks (Elasticsearch, OpenSearch, Solr), or vector databases.

Experience at a database, data platform, search, or AI infrastructure company (MongoDB, Snowflake, Databricks, Elastic, Confluent, Redis, Pinecone, AWS, GCP, Azure, or comparable).

Experience owning a performance, benchmark, or TCO narrative in a competitive market.

Public presence — blog posts, conference talks, OSS contributions, or analyst-facing work.

Prior experience mentoring associate or early-career PMs.

Who This Role Is Open To

Prior search, indexing or query product experience is genuinely not required. The domain is learnable in a quarter by someone with real systems instincts; the instincts themselves are not learnable on the job.

We expect strong candidates to come from adjacent areas: data platforms and warehouses, streaming and messaging, analytics, observability and monitoring, developer tools, API platforms, cloud infrastructure, or AI and ML infrastructure. Engineers who have moved into product management on a systems product are equally welcome.

What we will test for instead of domain history: how you reason about a performance or correctness tradeoff you have never seen before, how quickly you get to the right question when a customer describes a slow or wrong result, how you decide what to build and what to defer, and how well you write.

Location and Reporting

Based in Bangalore, India, working primarily from Couchbase’s Bangalore office with flexibility for hybrid work.