Head of AI-Native Product Operations

Lansweeper

Roma

On-site

EUR 45,000 - 70,000

Full time

14 days+

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Job summary

A leading technology company in Italy is seeking an experienced professional for a role in Product Operations. This unique position requires building AI-powered workflows and integrating various product functions. The ideal candidate will have over 5 years in product operations or a related field, hands-on experience with API integrations and orchestration platforms, and a strong understanding of B2B SaaS. Additionally, excellent English communication skills are vital for collaboration with cross-functional teams.

Qualifications

  • 5+ years in product operations or similar role.
  • Experience with AI-powered workflows in a professional context.
  • Hands-on with orchestration platforms and API integrations.

Responsibilities

  • Audit and map product workflow and toolchain.
  • Design and build AI-powered workflows using orchestration platforms.
  • Integrate product and engineering teams to streamline processes.
  • Collaborate with operations to align on product workflows.

Skills

Product operations
API integrations
Automation systems
Technical program management
B2B SaaS experience

Tools

Jira
Confluence
n8n
Zapier
Enterpret

Job description

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.
Core Attributes
  • A hands‑on builder. If something needs connecting, automating, or configuring, I do it myself. I get into the tools, build the workflows, and make things work.
  • Technically fluent. I'm comfortable with APIs, orchestration platforms, prompt engineering, vector databases, and connecting systems. Whether my background is in engineering, product, or operations, I bring the ability to build and ship working systems.
  • A systems thinker who sees how product management, UX, product marketing, enablement, and partner ecosystems connect, and how operational infrastructure can make those connections seamless.
  • Equally comfortable having a technical conversation about MCP integrations with Engineering, and a strategic conversation about product operating models with the CPO.
  • Someone who thrives in ambiguity. This is a greenfield role and I'm energized by that. I can assess the landscape, identify priorities, and start building from day one.
  • Passionate about enabling others. I build systems that make the people around me more effective, not systems that make me indispensable.
Required Experience
  • 5+ years in product operations, technical program management, solutions architecture, or a similar role in B2B SaaS.
  • A demonstrable track record of building AI‑powered workflows or automation systems in a professional context. Not just using AI tools, but designing, connecting, and maintaining multi‑step automated workflows.
  • Hands‑on experience with AI agent building, orchestration platforms (n8n, Make, Zapier), API integrations, MCP, vector databases, or similar technical infrastructure.
  • Deep familiarity with the product organization toolchain: Jira, Confluence, Pendo, Enterpret, or similar platforms.
  • Strong understanding of the B2B SaaS product development lifecycle across discovery, design, development, delivery, and go‑to‑market.
  • Experience working across both Engineering and GTM functions on process integration, tooling, and cross‑functional workflows.
  • A portfolio, GitHub repository, or other evidence of systems you've built. We value demonstrable building ability over certifications.
  • Excellent English communication skills (CEFR C1+). You can write documentation, present to leadership, and facilitate workshops with equal confidence.
Team Info

You will report directly to the Chief Product Officer and work across the entire product organization, collaborating daily with product managers, UX designers, product marketers, enablement specialists, and the partner ecosystem team. Engineering and the broader GTM organization are your primary collaboration partners, with Engineering being the most immediate priority. Your primary infrastructure partner is Lansweeper's internal Operations and IT team.

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