Head of AI-Native Product Operations

Context & Impact

For 21 years, Lansweeper has been a fast-moving company that is not afraid to reinvent itself. We've done so multiple times as the market, our product, and our customers have evolved. Now we're facing the biggest shift yet: the AI era. We're already well into it. Engineering is on the cutting edge of AI-assisted code development and QA, and product teams are widely using Claude Cowork, Atlassian Rovo, and other AI tools in their daily work. What's missing is the connective layer. Individual teams are adopting AI tools, but we lack the unified product workflows and tooling to turn that adoption into compounding, organization-wide returns. This role sits at the center of Product at Lansweeper and exists to build that layer: designing, configuring, and maintaining the product workflows, use cases, and product-owned tooling that sit on top of Lansweeper's shared company-wide AI and data foundation.

Challenge

• Greenfield mandate. No predecessor, no inherited toolkit, no established playbook. You define the discipline as you build it.

• Structural change, not evangelization. Lansweeper's teams are already bought in on AI. The challenge is driving rapid, coordinated change across product management, product marketing, UX, enablement, and the partner ecosystem to achieve higher economies of scale and prevent drift between functions.

• Two collaboration fronts. Engineering is the most advanced area and has the highest immediate need for process integration. At the same time, the interface between Product and the go-to-market organization needs to be sharper and more automated. Both require close partnership.

• Complex toolchain orchestration. Connecting agentic workflows across product planning, engineering, analytics, design, and communication platforms into reliable end-to-end systems.

• Defining success metrics in a discipline where industry benchmarks don't yet exist.

Key Responsibilities

• Audit and map the product organization's toolchain, workflows, and friction points across product management, product marketing, UX, enablement, and the partner ecosystem. Prioritize high-impact opportunities for AI-native automation.

• Design and build AI-powered workflows using orchestration platforms (n8n, Make, or equivalent), API integrations, and AI agents that replace manual coordination, reporting, and documentation. Own the full lifecycle from prototype to production.

• Work closely with Engineering to integrate and streamline the product-engineering interface: planning handoffs, sprint coordination, release management, QA feedback loops, and cross-functional reporting. This is where the most advanced adoption exists and the immediate need is highest.

• Build AI-native workflows for the interface between Product and the GTM organization, ensuring product context, competitive intelligence, and launch information flow cleanly across the boundary.

• Own and configure product-owned tools (e.g. Enterpret) and maintain a centralized product knowledge layer that makes context such as strategy, OKRs, architecture, personas, and competitive intelligence retrievable by AI agents and team members alike.

• Connect the product toolchain into automated workflows via APIs and MCP (Model Context Protocol), linking product planning, project management, analytics, design, and communication tools into a connected operating layer.

• Build and iterate on AI agents for product operations tasks: intake triage, PRD generation, status reporting, stakeholder perspective simulation, competitive analysis, and meeting preparation.

• Enable the product organization on AI-native workflows by designing onboarding, running workshops, creating guardrails and documentation, and building fluency across all product functions.

• Measure and report on operational impact (hours saved, cycle time, decision quality, adoption rates) and build dashboards that make the value of AI-native operations visible.

• Collaborate with Lansweeper's Operations and IT team to ensure product workflows and tooling are built on top of the shared company-wide AI and data foundation, aligning on security, governance, and enterprise-wide standards.

• Monitor the evolving AI tooling landscape, evaluate new platforms and models, and ensure Lansweeper's product operations infrastructure stays at the frontier.