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This is a principal-level, hands-on product leadership role owning end-to-end strategy, roadmap, and execution for a cross-cutting analytics portfolio at SingleStore. The role spans AI text-to-SQL and data analysis (Aura Analyst), AI and ML functions, query optimization and tuning, and database/cloud platform observability and alerting.
Key responsibilities include:
**Aura Analyst**: Own the primary end-user tool for AI-guided text-to-SQL and conversational query result analysis, including feature definition, customer positioning, and roadmap.
**AI & ML Functions Platform**: Co-own product strategy for AI and ML capabilities exposed as AI functions, ML functions, Python UDFs, Cloud Functions, Container Services, MCP servers, and AI documentation question answering. Ensure these surfaces are observable, testable, and debuggable with clear workflows for data engineers and developers.
**Query Optimization & Tuning**: Own product strategy for query optimization, tuning, and AI-based database tuning in collaboration with the core engine team. Define how query plans, regressions, and recommendations surface in UI, APIs, and internal tools. Partner with engine leadership on prioritization of investments that improve customer performance, reliability, and cost.
**Observability, Alerting & Internal Data Warehouse**: Own database observability, cloud container observability, and alerting experiences for both customers and internal SRE/support teams. Partner with data and analytics teams on internal product analytics and reporting stack.
The unifying theme is analytics—unlocking latent customer demand through AI-driven query and analysis, optimizing the core database engine for analytical workloads, and enabling analysis of system telemetry. A major company focus is surrounding SingleStore with AI assistance to make users more productive, allowing data to be queried and analyzed by a broader range of people, and making SingleStore increasingly self-observing, self-diagnosing, and self-optimizing.
Required experience includes multi-release roadmap development, deep technical understanding of databases and analytics, experience shipping AI/ML products, cross-functional collaboration with engineering and go-to-market teams, and a track record of building innovative, customer-centric products.
