Principal Product Manager Lead
singlestore · United States
Position Overview
This role is a principal-level, hands-on product leadership position in the Product organization. It 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 of this role is analytics, including unlocking latent demand in our customers using AI-driven query and analysis, making the core database engine perform analytical workloads better via query optimization, and enabling us and customers to analyze system telemetry to make workloads shine. If you love analytics, you're an experienced product leader, and want to build an innovative, AI-enriched product and business, not groom the backlog, this job is for you.
A major company focus is to surround SingleStore with AI assistance to make everyone using or building on SingleStore more productive. This includes allowing data to be queried and analyzed far more easily by a much broader range of people, and making SingleStore increasingly self-observing, self-diagnosing, and self-optimizing. This helps customers and internal teams use and analyze their data, understand workload behavior, debug issues quickly, and continuously improve performance and efficiency. This role leads product management for a range of AI analysts, skills, and MCP servers to provide these capabilities.
## Role and Responsibilities
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 that 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 we have 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.
Experience quality and cohesion
• 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.
## 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.
SingleStore delivers the cloud-native database with the speed and scale to power the world’s data-intensive applications. With a distributed SQL database that introduces simplicity to your data architecture by unifying transactions and analytics, SingleStore empowers digital leaders to deliver exceptional, real-time data experiences to their customers. SingleStore is venture-backed and headquartered in San Francisco with offices in Sunnyvale, Raleigh, Seattle, Boston, London, Lisbon, Bangalore, Dublin and Kyiv.
Consistent with our commitment to diversity & inclusion, we value individuals with the ability to work on diverse teams and with a diverse range of people.
To all recruitment agencies: SingleStore does not accept agency resumes. Please do not forward resumes to SingleStore employees. SingleStore is not responsible for any fees related to unsolicited resumes and will not pay fees to any third-party agency or company that does not have a signed agreement with the Company.
SingleStore values individuals for their unique skills and experiences, and we’re proud to offer roles in a variety of locations across the United States. Salary is based on permissible, non-discriminatory factors such as skills, experience, and geographic location, and is just one part of our total compensation and benefits package. Certain roles are also eligible for additional rewards, including merit increases and annual bonuses.
SingleStore’s total compensation range for this role, if based in Boston, Chicago, New York, Austin, Phoenix, Las Vegas, Seattle, Washington, or Dallas is:
00,000 -
75,000 USD per year
For candidates residing in California, please see our California Recruitment Privacy Notice . For candidates residing in the EEA, UK, and Switzerland, please see our EEA, UK, and Swiss Recruitment Privacy Notice.
This role is a principal-level, hands-on product leadership position in the Product organization. It 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 of this role is analytics, including unlocking latent demand in our customers using AI-driven query and analysis, making the core database engine perform analytical workloads better via query optimization, and enabling us and customers to analyze system telemetry to make workloads shine. If you love analytics, you're an experienced product leader, and want to build an innovative, AI-enriched product and business, not groom the backlog, this job is for you.
A major company focus is to surround SingleStore with AI assistance to make everyone using or building on SingleStore more productive. This includes allowing data to be queried and analyzed far more easily by a much broader range of people, and making SingleStore increasingly self-observing, self-diagnosing, and self-optimizing. This helps customers and internal teams use and analyze their data, understand workload behavior, debug issues quickly, and continuously improve performance and efficiency. This role leads product management for a range of AI analysts, skills, and MCP servers to provide these capabilities.
## Role and Responsibilities
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 that 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 we have 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.
Experience quality and cohesion
• 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.
## 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.
SingleStore delivers the cloud-native database with the speed and scale to power the world’s data-intensive applications. With a distributed SQL database that introduces simplicity to your data architecture by unifying transactions and analytics, SingleStore empowers digital leaders to deliver exceptional, real-time data experiences to their customers. SingleStore is venture-backed and headquartered in San Francisco with offices in Sunnyvale, Raleigh, Seattle, Boston, London, Lisbon, Bangalore, Dublin and Kyiv.
Consistent with our commitment to diversity & inclusion, we value individuals with the ability to work on diverse teams and with a diverse range of people.
To all recruitment agencies: SingleStore does not accept agency resumes. Please do not forward resumes to SingleStore employees. SingleStore is not responsible for any fees related to unsolicited resumes and will not pay fees to any third-party agency or company that does not have a signed agreement with the Company.
SingleStore values individuals for their unique skills and experiences, and we’re proud to offer roles in a variety of locations across the United States. Salary is based on permissible, non-discriminatory factors such as skills, experience, and geographic location, and is just one part of our total compensation and benefits package. Certain roles are also eligible for additional rewards, including merit increases and annual bonuses.
SingleStore’s total compensation range for this role, if based in Boston, Chicago, New York, Austin, Phoenix, Las Vegas, Seattle, Washington, or Dallas is:
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- CAP Theorem · advance
- Rate Limiting · advance
- Service Discovery · advance
- Event-Driven Architecture · advance
- API Gateway · advance
- Distributed Consensus · expert
- Microservices · expert
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- PACELC Theorem · expert
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- readline, timers & scheduling · medium
- Testing & diagnostics (intro) · medium
- Worker threads · advance
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Public study materials
- Express.js — Web APIs & middleware (expressjs)
- Application setup · basic
- Routing deep dive · basic
- 1. MVC / Layered Architecture · medium
- Validation · medium
- File uploads · medium
- Sessions & auth (stateful) · medium
- Passport & strategies · medium
- Templating & SSR · medium
- WebSockets & SSE · medium
- Security middleware · advance
- Reverse proxies & trust · advance
- Performance · advance
- API design & versioning · advance
- Testing with Supertest · advance
- GraphQL & tRPC (overview) · advance
- Deployment checklist · advance
- Middlewares · basic
- Request & Response · basic
- AWS Crash Course (AWS)
- What is Cloud ? · basic
- What is AWS ? · basic
- If not cloud ? · basic
- Cloud Computing · basic
- AWS Pricing · basic
- AWS Shared Responsibility Model · basic
- AWS Management Console · basic
- AWS SDKs · basic
- AWS IAM · medium
- Users, Groups, Roles · medium
- Policies · medium
- AWS Organizations · medium
- AWS Cognito · medium
- AWS Directory Service · medium
- AWS KMS (Key Management Service) · medium
- AWS Secrets Manager · medium
- AWS Shield · medium
- AWS WAF · medium
- AWS Inspector · medium
- AWS GuardDuty · medium
- EC2 · advance
- Launching EC2 Instances · advance
- EBS Volumes · advance
- Security Groups · advance
- Key Pairs · advance
- Elastic IP · advance
- User Data Scripts · advance
- Auto Scaling · advance
- Load Balancers · advance
- ALB · advance
- NLB · advance
- Serverless Compute ,AWS Lambda, Lambda Layers · advance
- Event-Driven Architecture · advance
- ECS · advance
- EKS · advance
- Django (Django)
- What is Django · basic
- Installing Django · basic
- Features of Django · basic
- MVT Architecture · basic
- Django vs Flask · basic
- Creating Project & Creating App · basic
- Django Project Structure · basic
- URL Routing · basic
- Views · basic
- Templates · basic
- Static & Media Files · medium
- Models · medium
- ORM (Object Relational Mapping) · medium
- Model Relationships · medium
- Migrations · medium
- Django Admin · medium
- Forms · medium
- Authentication · medium
- Authorization · medium
- Middleware · medium
- Signals · medium
- Class Based Views Deep Dive · advance
- Generic Views · advance
- File Handling · advance
- Django REST Framework (DRF) · advance
- Advanced ORM · advance
- Caching · advance
- Asynchronous Django · advance
- Background Tasks · advance
- Interview Questions · interview-questions
- System Designing (System Designing)
- Day-1 : What is system Designing ? · basic
- Day-2 : Vertical vs. Horizontal Scaling · basic
- Day-3:How to do vertical scaling ? · basic
- Day4:How to do horizaontal scaling ? · basic
- Day:5TCP vs UDP · basic
- Day6:IP & DNS · basic
- Day7:Client-Server Model · basic
- Day8:HTTP & HTTPS · basic
- Databases (SQL vs NoSQL) · medium
- Caching · medium
- Day9:Latency & Throughput · basic
- Load Balancing · medium
- Indexes & Query Optimization · medium
- CDN · medium
- Proxies · medium
- Message Queues · medium
- Horizontal vs Vertical Scaling · medium
- Database Replication · advance
- Database Sharding · advance
- Consistent Hashing · advance
- CAP Theorem · advance
- Rate Limiting · advance
- Service Discovery · advance
- Event-Driven Architecture · advance
- API Gateway · advance
- Distributed Consensus · expert
- Microservices · expert
- Observability · expert
- Idempotency · expert
- PACELC Theorem · expert
- Two-Phase Commit · expert
- Back-of-Envelope Estimation · expert
- Designing for Failure · expert
- Node.js — Server-side JavaScript (nodejs)
- Getting started · basic
- JavaScript on the server · basic
- CommonJS modules · basic
- ES modules (ESM) · basic
- npm & package management · basic
- Asynchronous JavaScript in Node · basic
- The event loop · basic
- Essential core utilities · basic
- process & configuration · basic
- File system basics · basic
- HTTP & HTTPS servers · medium
- Streams · medium
- Events & EventEmitter · medium
- Advanced filesystem · medium
- crypto · medium
- Compression & encoding · medium
- Child processes · medium
- net, dgram & DNS · medium
- readline, timers & scheduling · medium
- Testing & diagnostics (intro) · medium
- Worker threads · advance
- cluster & multi-process scaling · advance
- Performance & tuning · advance
- Debugging & observability · advance
- Security hardening · advance
- Native addons & N-API · advance
- Architecture patterns · advance
- Graceful shutdown · advance
- 100 Questions · interview questions
- Python (Python)
- Python Fundamentals · basic
- Control Flow · basic
- Strings · basic
- Collections / Data Structures · basic
- Functions · basic
- Modules and Packages · basic
- File Handling · basic
- Exception Handling · basic
- Object-Oriented Programming (OOP · medium
- Advanced Python Concepts · advance
- Functional Programming · advance
- Multithreading & Multiprocessing · advance
- Async Programming · advance
- JavaScript (JavaScript)
- JS Introduction · basic
- Variables & Data Types · basic
- Operators · basic
- Control Flow · basic
- Functions · basic
- Scope & Execution · basic
- Closures · basic
- Objects · basic
- Arrays · basic
- Strings · basic
- DOM Manipulation · basic
- Browser APIs · medium
- Asynchronous JavaScript · medium
- Fetch & APIs · medium
- ES6+ Features · medium
- OOP in JavaScript · medium
- Prototype & Inheritance · advance
- Advanced Functions · advance
- Memory Management · advance
- Error Handling · advance
- Modules · advance
- Advanced Async Concepts · advance
- Functional Programming · advance
- JavaScript Internals · advance
- Performance Optimization · advance
- MongoDB — Documents & data modeling (MongoDB)
- Introduction · basic
- Shell, Compass & tools · basic
- Databases & collections · basic
- CRUD operations · basic
- Indexes deep dive · medium
- Explain plans & performance · medium
- Aggregation framework · medium
- Schema design patterns · medium
- Mongoose basics · medium
- Mongoose advanced · medium
- Drivers & connection · medium
- Operators for updates & arrays · medium
- Replication & read preferences · advance
- Write concern & read concern · advance
- Multi-document transactions · advance
- Change streams · advance
- Sharding (overview) · advance
- Atlas Search & full-text · advance
- GridFS & large files · advance
- Backup, restore & ops · advance
- SQL (SQL)
- SQL Fundamentals · basic
- Database Operations · basic
- Table Operations · basic
- CRUD Operations · basic
- Filtering & Operators · basic
- SQL Functions · basic
- GROUPING Data · basic
- Joins · medium
- Constraints · basic
- Subqueries · medium
- Set Operators · medium
- Views · medium
- Indexes · medium
- Normalization · advance
- Transactions · advance
- Stored Procedures & Functions · advance
- Triggers · advance
- Advanced SQL · advance
- Query Optimization · advance
- Database Design · advance
- SQL Security · advance
- Backup & Recovery · advance
- Questions · interview questions
- System Architecture (System Architecture)
- Fundamentals of System Architecture · basic
- Distributed System Basics · basic
- System Reliability Concepts · basic
- Scaling Concepts · basic
- Networking Basics · basic
- Web Communication · basic
- API Communication · basic
- Proxy & Delivery Systems · basic
- Web Architecture Basics · basic
- Rendering Architectures · basic
- Frontend Advanced Concepts · basic
- Message Queue Basics · medium
- What is Load Balancer · medium
- Load Balancing Algorithms · medium
- API Design Basics · medium
- API Protection · medium
- Authentication Basics · medium
- Security Tokens · medium
- Security Threats · medium
- Encryption & Security · medium
- SQL Database Basics · medium
- SQL Scaling Concepts · medium
- NoSQL Databases · medium
- Database Optimization · medium
- Replication Strategies · medium
- Caching Basics · medium
- Cache Storage Systems · medium
- Cache Strategies · medium
- Event-Driven Systems · advance
- Queue Reliability · advance
- Microservices Basics · advance
- Microservice Communication · advance
- Distributed Transactions · advance
- DevOps Basics · advance
- Automation Tools · advance
- Deployment Strategies · advance
- Monitoring Basics · advance
- Monitoring Tools · advance
- Distributed System Concepts · advance
- Distributed Algorithms · advance
- Angular (Angular)
- Angular Fundamentals · basic
- Project Structure · basic
- Components & Templates · basic
- Data Binding · basic
- Directives · basic
- Pipes · basic
- Component Communication · basic
- Lifecycle Hooks · basic
- Routing Basics · basic
- Routing · basic
- API Calls · basic
- Forms · medium
- Routing · medium
- Services & Dependency Injection · medium
- RxJS & Observables · medium
- Authentication & Security · medium
- Component Interaction · medium
- State Management Basics · medium
- Error Handiling · medium
- Perfomance Basic · medium
- Real World Features · medium
- Advanced Angular Architecture · advance
- Change Detection · advance
- Advanced RxJS · advance
- State Management · advance
- Dynamic Rendering · advance
- Perfomance Optimization · advance
- Modern Angular · advance
- STAR (Situation, Task, Action, and Result) (Situation Based Questions)
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