Principal Product Manager Lead

About the role

This principal-level, hands-on product leadership role owns the end-to-end strategy, roadmap, and execution for a cross-cutting portfolio spanning AI text-to-SQL and data analysis (Aura Analyst), AI and ML functions, query optimization and tuning, and database/cloud platform observability & alerting. A unifying theme is analytics: unlocking latent demand via AI-driven query and analysis, improving analytical workload performance through query optimization, and enabling telemetry-driven analysis for both customers and internal teams. The role focuses on building an innovative, AI-enriched product and business, not backlog grooming.

SingleStore’s focus is to surround the database with AI assistance to make users more productive, enabling easier querying and analysis for a broader audience and making SingleStore self-observing, self-diagnosing, and self-optimizing. This helps customers and internal teams analyze data, understand workload behavior, debug issues quickly, and continuously improve performance and efficiency. The role leads product management for AI analysts, skills, and MCP servers that deliver these capabilities.

Primary product areas

• Aura Analyst: 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.
• AI & ML Functions Platform: 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 AI workloads are first-class citizens in observability and performance views.
• Query Optimization & Tuning: 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.
• Observability, Alerting & Internal Data Warehouse: 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.

Required Skills And Experience

Strategy & roadmap

• 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.

Cross-functional leadership & people management

• 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.

Customer, field, and internal stakeholder engagement

• 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.

Execution and delivery

• 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 clear “definition of done” and acceptance criteria for features in this portfolio.

Metrics and continuous improvement

• 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.

Expected Profile and Skills

• 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.

Pay

SingleStore’s total compensation range for this role, if based in Boston, Chicago, New York, Austin, Phoenix, Las Vegas, San Francisco, Seattle, Washington, or Dallas is: $200,000 – $275,000 USD per year. Salary is based on permissible, non-discriminatory factors such as skills, experience, and geographic location, and is part of a total compensation and benefits package. Certain roles are also eligible for additional rewards, including merit increases and annual bonuses.