Principal Product Manager Lead

SingleStore is a cloud-native database company that empowers digital leaders to deliver exceptional, real-time data experiences. The Principal Product Manager Lead will own the strategy, roadmap, and execution for a portfolio that includes AI text-to-SQL and data analysis, focusing on enhancing product capabilities and customer engagement through innovative analytics solutions.

Responsibilities:

• Owns Aura Analyst as the primary end-user tool for AI-guided text-to-SQL and conversational query result analysis, including technical feature set definition, customer positioning, and roadmap
• Co-owns the product strategy for AI and ML capabilities exposed as AI functions, ML functions, Python UDFs, Cloud Functions, Container Services, MCP server, and AI documentation question answering (SQrL)
• Ensures these surfaces are observable, testable, and debuggable, with clear workflows for data engineers and application developers
• Aligns AI/ML function capabilities with Aura Analyst so that AI workloads are first-class citizens in observability and performance views
• Owns product strategy for query optimization, tuning, and AI-based database tuning, in close collaboration with the core engine team
• Defines how query plans, regressions, and recommendations are surfaced in the UI, APIs, and internal tools
• Partners with engine leadership on prioritization of query engine investments that materially improve customer performance, reliability, and cost
• Owns database observability, cloud containers observability, and alerting experiences used by both customers and internal SRE/support teams
• Partners with data and analytics teams on the internal product analytics and reporting stack powering dashboarding on product adoption and COGS
• Develops and maintains a multi-release roadmap for Aura Analyst, SingleStore productivity AI Agents, skills and MCP servers, AI/ML functions, query optimization, and observability & alerting, aligned with company strategy and product positioning
• Defines clear problem statements, success criteria, and scope for major initiatives; maintains a prioritized backlog across teams
• Acts as the product lead across multiple engineering and design teams (engine, cloud, AI platform, SRE, support, DevX)
• Directly manages an analytics engineer responsible for building and maintaining reporting on cloud platform operations, product usage, and key business metrics; provides prioritization, feedback, and career coaching
• Provides product direction and mentorship to PMs working in adjacent areas (AI, DevX, analytics)
• Ensures initiatives in this portfolio are well understood and sequenced appropriately in planning cycles
• Regularly meets with key customers and design partners to validate problems, designs, and proposed solutions in this portfolio
• Serves as a primary point of contact for the field (Sales, Solutions, CS) on performance, observability, and AI-diagnostics-related topics
• Partners with Support and SRE to translate recurring operational pain (e.g., incidents, hot spots, noisy alerts) into product requirements
• Writes product requirements documents and detailed requirements for new features and enhancements; reviews technical design documents and UX designs to ensure alignment with product goals
• Drives end-to-end feature delivery: preview programs, documentation coordination, field enablement, and launch readiness
• Ensures we have clear “definition of done” and acceptance criteria for features in this portfolio
• Defines and tracks key metrics and leading indicators, including (examples, not exhaustive): Time-to-detect (TTD) and time-to-resolve (TTR) for incidents; Query performance and resource efficiency metrics (CPU, memory, GPU); Adoption, engagement, and retention for Aura Analyst and AI/ML functions; Volume and severity of support tickets related to performance and observability
• Works with analytics and data engineering teams to ensure telemetry, internal views, and dashboards exist to measure these outcomes
• Uses data and qualitative feedback to iterate on UX, feature behavior, and defaults
• Ensures experiences across Aura Analyst, AI functions, query insights, and observability feel cohesive, not separate tools, especially for workflows like: AI-guided querying and analysis; Debugging slow queries or incidents; Understanding resource consumption and cost; Operating AI and ML features in production

Requirements:

• Develops and maintains a multi-release roadmap for Aura Analyst, SingleStore productivity AI Agents, skills and MCP servers, AI/ML functions, query optimization, and observability & alerting, aligned with company strategy and product positioning
• Defines clear problem statements, success criteria, and scope for major initiatives; maintains a prioritized backlog across teams
• Acts as the product lead across multiple engineering and design teams (engine, cloud, AI platform, SRE, support, DevX)
• Directly manages an analytics engineer responsible for building and maintaining reporting on cloud platform operations, product usage, and key business metrics; provides prioritization, feedback, and career coaching
• Provides product direction and mentorship to PMs working in adjacent areas (AI, DevX, analytics)
• Ensures initiatives in this portfolio are well understood and sequenced appropriately in planning cycles
• Regularly meets with key customers and design partners to validate problems, designs, and proposed solutions in this portfolio
• Serves as a primary point of contact for the field (Sales, Solutions, CS) on performance, observability, and AI-diagnostics-related topics
• Partners with Support and SRE to translate recurring operational pain (e.g., incidents, hot spots, noisy alerts) into product requirements
• Writes product requirements documents and detailed requirements for new features and enhancements; reviews technical design documents and UX designs to ensure alignment with product goals
• Drives end-to-end feature delivery: preview programs, documentation coordination, field enablement, and launch readiness
• Ensures we have clear 'definition of done' and acceptance criteria for features in this portfolio
• Defines and tracks key metrics and leading indicators, including (examples, not exhaustive): Time-to-detect (TTD) and time-to-resolve (TTR) for incidents, Query performance and resource efficiency metrics (CPU, memory, GPU), Adoption, engagement, and retention for Aura Analyst and AI/ML functions, Volume and severity of support tickets related to performance and observability
• Works with analytics and data engineering teams to ensure telemetry, internal views, and dashboards exist to measure these outcomes
• Uses data and qualitative feedback to iterate on UX, feature behavior, and defaults
• Ensures experiences across Aura Analyst, AI functions, query insights, and observability feel cohesive, not separate tools, especially for workflows like: AI-guided querying and analysis, Debugging slow queries or incidents, Understanding resource consumption and cost, Operating AI and ML features in production
• Deep understanding of distributed databases, query processing, and performance optimization, with comfort reading query plans, indexes, and workload patterns
• Working knowledge of, and experience delivering AI Agents, skills, and/or MCP servers
• Strong familiarity with observability and alerting systems and SRE/operations workflows
• Demonstrated ability to work effectively with senior engineering leaders and architects on complex technical decisions and trade-offs
• Strong execution skills: able to drive complex, multi-quarter initiatives across multiple teams while maintaining clarity on goals, ownership, and status
• Excellent communication skills, with the ability to present complex technical topics to executives, field teams, and customers in a clear, outcome-oriented way
• Willingness and ability to mentor other PMs and act as a go-to leader for performance, diagnostics, and AI/observability-related product questions