Senior Director, Product Management – Database Business Unit

The Senior Director, Product Management leads product strategy, roadmap, and execution for the SolarWinds Database Business Unit—a portfolio that includes SQL Sentry, Database Performance Analyzer, and Database Observability delivered through SolarWinds Observability SaaS. Our customers are DBAs, data platform engineers, and the application teams who depend on them, at organizations where a slow query is a revenue event.

This is a rare combination of portfolio ownership, domain depth, and reinvention. The database market is being reshaped by AI on two fronts at once: customers are racing to make their data estates AI-ready, and the work of database administration itself is shifting from human-driven triage toward agentic diagnosis and remediation. You will set the point of view that determines where SolarWinds plays in that shift, and you will run a product organization that builds the way it preaches—partnering with engineering in an AI-Driven Development Lifecycle (AI-DLC) model and using AI throughout the product management craft itself.

You will lead and grow a team of product managers, own the portfolio P&L in partnership with BU leadership, and serve as the executive voice of the database business with customers, analysts, partners, and the field.

Key Responsibilities

• Own the multi-year strategy and roadmap for the database portfolio across self-hosted and SaaS delivery, spanning SQL Server, Oracle, PostgreSQL, MySQL, Db2, SAP ASE, and cloud-native and NoSQL platforms.
• Define the portfolio thesis: where we differentiate, where we integrate, where we partner, and where we sunset—and make the trade-offs explicit and defensible to the executive team.
• Drive the convergence strategy that brings depth-of-domain database capability into the broader SolarWinds Observability platform without diluting what DBAs value most about our products.
• Own portfolio business outcomes in partnership with BU leadership: ARR growth, net revenue retention, adoption and expansion, pricing and packaging, and margin.
• Build and defend the investment case for new bets through sizing, competitive analysis, and buy/build/partner evaluation, and present recommendations to the executive staff.
• Establish a rigorous, evidence-driven discovery practice—customer advisory boards, THWACK community engagement, win/loss analysis, telemetry, and direct DBA immersion—so roadmap decisions rest on evidence rather than opinion.

AI Thought Leadership

• Set and evangelize a forward-leaning point of view on how AI changes database management: agentic troubleshooting, natural-language query and performance analysis, autonomous tuning recommendations, anomaly detection, and predictive capacity and cost optimization.
• Define the SolarWinds position on AI readiness for the data estate—how customers instrument, govern, and prepare the databases that now serve AI workloads—and translate that position into shipped capability, not just narrative.
• Establish the trust framework for AI in the product: explainability, guardrails on write and remediation actions, data residency and privacy, model transparency, and the human-in-the-loop boundaries that enterprise DBAs will require before they delegate anything.
• Represent SolarWinds externally as a credible technical voice—with analysts, at industry and data platform events, in the THWACK community, and with strategic customers—and bring that market signal back into the roadmap.
• Partner with Product Marketing to convert the AI point of view into positioning, packaging, monetization models, and field enablement that sales can carry.

AI-Native Product Management Practice

• Use AI as a core instrument of the product management craft, not a side experiment: synthesizing customer and support signal at scale, mining product telemetry, accelerating competitive and market research, drafting and pressure-testing requirements, and prototyping concepts before committing engineering capacity.
• Build the AI operating model for the product organization—tooling, prompts and agents, evaluation habits, and quality bars—so the team moves faster without lowering the standard of judgment applied to decisions.
• Coach the team on where AI accelerates the work and where it must not substitute for direct customer contact, domain reasoning, or accountability for outcomes.
• Instrument the practice: define how the organization measures cycle time from insight to validated requirement, and demonstrate compounding improvement.

Engineering Partnership in an AI-DLC Model

• Partner with engineering leadership to operate an AI-Driven Development Lifecycle in which intent, specifications, and acceptance criteria—not hand-written tickets—are the primary product artifacts that drive execution.
• Raise the precision of product inputs to match the model: write intent and specifications that are unambiguous enough to drive agentic planning, implementation, and test generation, with humans holding decision rights and review authority.
• Work with engineering to reshape the planning cadence, definition of done, and quality gates around AI-assisted delivery—including how validation, security review, and customer verification keep pace with faster code generation.
• Maintain the product organization’s accountability for outcomes rather than output, ensuring that increased delivery velocity converts into customer value and measurable business results.
• Collaborate closely with UX, architecture, QA, support, and security to deliver releases that meet SolarWinds Secure by Design standards.

Leadership and Cross-Functional Influence

• Lead, hire, and develop a high-performing, geographically distributed team of product managers; set clear expectations, raise the bar on craft, and build a bench of future product leaders.
• Create a culture of accountability, customer obsession, and intellectual honesty in which strong opinions are welcomed and data settles disagreements.
• Serve as the connective tissue across Engineering, Product Marketing, Sales, Customer Success, Support, and Finance to align the portfolio behind a single plan.
• Support strategic sales and renewal opportunities as the executive product sponsor, and equip the field with the narrative, proof points, and roadmap transparency needed to win.
• Communicate portfolio strategy, progress, and risk clearly and frequently to executive leadership.

Qualifications

• 10+ years in product management with 5+ years leading product teams, including experience managing managers or senior individual contributors in a distributed organization.
• Demonstrated ownership of a software portfolio or business line with accountability for revenue, retention, and investment decisions—not solely feature-level roadmap ownership.
• Deep domain experience in databases, data platforms, or database/application performance management. Direct familiarity with relational and cloud database internals—query execution, wait states, indexing, and performance tuning—and credibility with a DBA audience.
• Experience in observability, monitoring, IT operations management, or enterprise infrastructure software; experience shipping both self-hosted and SaaS products strongly preferred.
• Demonstrated fluency with AI and machine learning applied to products: LLM and agentic capabilities, anomaly detection, evaluation methods, and the trust, cost, and governance considerations that determine whether enterprises adopt them.
• Hands-on use of AI tooling in the product management workflow, with concrete examples of how it changed the team’s speed or quality of decision-making.
• Experience partnering with engineering in AI-assisted or AI-driven development models (AI-DLC, spec-driven development, or equivalent), including how product artifacts and quality gates must change to support them.
• Track record of translating a market point of view into a shipped roadmap and measurable commercial results.
• Exceptional written and verbal communication with executive presence; proven ability to influence without authority across a matrixed, global organization.
• Bachelor’s degree in a technical discipline or equivalent practical experience; advanced degree a plus.
• Willingness to travel up to 20% for customer, partner, and industry engagements.

Preferred Experience

• Prior experience as a DBA, data platform engineer, or database consultant.
• Experience integrating an acquired or standalone product into a broader platform.
• Established presence in the data platform community—speaking, writing, or open-source contribution.
• Experience with usage-based or consumption pricing models for observability or data products.