Product Manager

WHAT YOU WILL OWN

1. Internal platform product roadmap

• Own the product strategy and roadmap for CIMET's internal platform layer: the tools, consoles, dashboards, and workflow systems used by Operations, Finance, Partner Management, CX, and the Product team itself.
• Before defining what to build, map how the system works end-to-end: where data originates, how it moves between teams and tools, where it breaks or gets duplicated, and what the downstream consequences of each failure point are.
• Define what gets built, upgraded, automated, or eliminated. Prioritise based on system-level impact: not just time saved in one team, but friction and error removed from the broader operating chain.
• Maintain a live inventory of current internal tools and workflows with an honest assessment of what is working, what is broken, what is redundant, and what creates hidden dependencies that any change must account for.
• Set quarterly targets for workflow automation coverage and manual effort reduction, and report against them.

2. System redesign before automation

• Treat automation as the second step, not the first. Before any workflow is automated, establish whether the workflow is worth automating: is it structured correctly, does it have the right inputs, does it produce the right outputs, or does it need to be redesigned first?
• Map process interdependencies across teams before making changes. Understand what each workflow receives from upstream and delivers downstream, so that a change in one area does not create invisible breakage elsewhere.
• Identify where manual workarounds have become load-bearing: processes that exist only because a system gap was never fixed, that now have teams depending on them. These need redesign, not automation.
• Define data standards and workflow contracts at the system level: what information flows between teams, in what format, at what frequency, with what quality guarantees. Automation built without these contracts creates fragile pipelines.
• Own the transition from current state to redesigned state: sequencing changes so that teams are not left without working processes during the shift, and so that new automations land on a clean foundation.

3. Automation and AI implementation

• Identify and implement rules-based automation across high-frequency, high-friction internal workflows using n8n. Own the automation backlog end-to-end: scoping, requirement definition, implementation coordination, testing, and rollout.
• Identify where GenAI integration materially improves an internal workflow: document processing, lead quality assessment, report generation, exception triaging, or communication drafting. Specify the product requirements, not just the use case.
• Manage CIMET's internal agentic AI programme: multi-step workflows where AI agents take autonomous actions across systems. Define what agents should own, what their boundaries are, what the human-in-the-loop checkpoints are, and how failures are caught.
• Maintain rigorous output quality standards for every AI-assisted workflow: accuracy benchmarks, fallback handling, escalation paths, and monitoring dashboards. No AI workflow ships without a defined quality floor and observable telemetry.

4. Internal tooling upgrades

• Own the upgrade agenda for existing internal tools: partner management consoles, operations dashboards, agent tooling, finance and reconciliation systems, and reporting infrastructure.
• Evaluate each tool upgrade in its system context: what does this tool receive from other systems, what does it feed into, and does the upgrade create or remove integration points that affect the broader platform?
• Define clear upgrade briefs: what the current tool does poorly, what the new experience should deliver, what success looks like in measurable terms.
• Partner with engineering to ensure internal tool upgrades are built to platform standards: no bespoke one-off builds that create maintenance debt or system fragmentation.
• Own UAT for internal product launches: coordinate with operational teams, define acceptance criteria, and do not sign off on releases that do not meet the bar.

5. Cross-functional stakeholder management

• Serve as the primary product contact for internal business functions on their tooling and automation needs. Understand their workflows deeply enough to form an independent point of view on what they actually need versus what they think they want.
• Run structured discovery with operational teams: map workflows, identify friction points, surface cross-team dependencies that stakeholders cannot see from inside their own function, and prioritise by ROI at the system level.
• Manage competing stakeholder priorities without letting every team get whatever they ask for. Maintain a transparent prioritisation framework that internal teams can see and challenge.
• Communicate roadmap, delivery status, and outcomes to senior stakeholders with enough clarity that decisions can be made without needing to dig into detail.

6. Automation ROI tracking

• Define and track the business case for every automation initiative: hours saved per week, error rate before and after, cycle time reduction, and cost impact where quantifiable.
• Produce a quarterly Internal Platform ROI summary covering what shipped, what it delivered, and what the pipeline looks like for the next quarter.
• Build the internal case for continued investment in platform automation by making the outcomes visible to leadership.

Experience required

• 4 to 5 years of product management experience with a strong weighting toward platform products, internal tools, or workflow automation.
• Has done system-level process analysis before: mapped how work actually flows across a business, identified where the real bottlenecks sit versus where they appear to sit, and redesigned processes rather than paving over broken ones. Can show a specific example.
• Has shipped automation in production: rules-based workflows, integrations between internal systems, or AI-assisted process automation with measurable business outcomes. Not prototypes or POCs. Shipped, monitored, and iterated on in production.
• Has worked directly with n8n, Zapier, Make, or a comparable workflow orchestration platform at a product ownership level, not just as a user.
• Has specified and delivered at least one GenAI integration into an internal or operational workflow. Can describe the input/output definition, quality thresholds, fallback behaviour, and how accuracy was measured.
• Has managed cross-functional internal stakeholders with competing priorities and held a product position under pressure. Not a requirements gatherer.
• Consumer tech, marketplace, fintech, or comparable product-led organisation background preferred.

Technical fluency required

• Comfortable specifying integrations as product requirements: what data is exchanged, what triggers the call, what the error handling should be, and what the monitoring looks like.
• Can read and interrogate a data model, event schema, or SQL query well enough to catch problems in product specifications before they become engineering rework.
• Working familiarity with n8n at a depth sufficient to scope what is automatable without needing engineering to sanity-check every idea. Zapier or Make acceptable if n8n is a quick ramp.
• Hands-on experience with LLM APIs or GenAI tooling in a product context: Claude, OpenAI, or equivalent. Understands prompt architecture, output variability, and evaluation at a product level.
• Familiarity with observability and monitoring concepts: knows what to instrument in an automated workflow and what a healthy versus degraded automation looks like in a dashboard.

Capabilities and ways of working

• Systems thinker: sees how parts connect before deciding what to change. Asks what is upstream, what is downstream, and what breaks if this moves. Resists automating processes that are structurally wrong. Looks for root causes, not symptoms.
• Outcome-first: measures everything in time saved, error reduced, cycle shortened. Never describes success as 'we shipped the workflow.'
• Technically credible: can sit with an engineering team and have a peer-level conversation about system design, integration architecture, and automation reliability.
• Stakeholder spine: forms an independent view of what internal teams need and defends it. Does not let the loudest business stakeholder set the roadmap. Can hold the system view when individual teams push for local optimisations that would create global fragmentation.
• Bias to production: treats a working automation in production as the only valid deliverable. Not a documentation-first or strategy-deck PM.
• AI-native practice: uses AI tools daily in their own product work: for research, spec writing, workflow design, and analysis. Does not need to be convinced that AI belongs in their toolkit.

Tools

• n8n (required), Zapier or Make acceptable with demonstrated depth.
• Jira and Confluence for delivery tracking and documentation.
• SQL for querying operational data to validate automation performance and identify workflow bottlenecks.
• LLM APIs (Claude, OpenAI, or equivalent) in working product contexts.
• Postman or equivalent for API testing and integration validation.
• Amplitude, Mixpanel, Grafana, or equivalent for monitoring automated workflows post-launch.

Education

• Bachelor's degree in Engineering, Computer Science, required.