Product Manager

About Keyloop

Purpose of the Role

Key Responsibilities

AI-First Product Thinking

• Use of AI in your own product management practice. Use LLM-based assistants, copilots, and automated analysis tools daily — for competitive research, requirements synthesis, data analysis, stakeholder communication drafting, and backlog refinement. If a task can be done faster or better with AI, you should already be doing it that way.
• Challenge the status quo on every reporting and insight workflow you encounter. Ask “why is this still a manual export or a static dashboard?” and “what would this look like if we built it AI-first?” — whether it is liveboard design, natural-language querying, anomaly detection, or cross-hub data reconciliation.
• Stay deeply current with AI developments in enterprise SaaS, analytics, and business intelligence. Bring informed, opinionated perspectives to the team on where AI creates genuine advantage and where it introduces risk — including accuracy thresholds for automated insight, data trust, and explainability of AI-generated answers.
• Champion responsible AI adoption across the product organisation, ensuring AI-driven features meet GDPR, accuracy, and transparency standards — while pushing back on the instinct to over-govern innovation before it has been tested.
• Influence the broader product team to think differently about how AI changes the economics and experience of product delivery itself — from AI-assisted grooming and specification writing to automated testing, release analysis, and customer feedback synthesis.

Roadmap & Strategy

• Own and communicate the product roadmap, aligning it with Keyloop’s broader platform strategy (Fusion, ADC, and VEGA.ai).
• Translate market signals, customer feedback, hub product requirements, and data platform constraints into a prioritised set of themes, initiatives, and epics.
• Participate in and influence PI (Program Increment) planning cycles, ensuring your product area’s priorities are well-represented and clearly justified.
• Make deliberate trade-off decisions between new feature development, technical debt reduction, platform modernisation, and data governance obligations.
• Develop and maintain a clear view of the competitive landscape in embedded analytics and business intelligence, identifying opportunities for differentiation across Keyloop’s retailer and enterprise markets.

Backlog & Delivery

• Own and groom the engineering team’s backlog directly — working closely with the team, day to day, to keep it well-prioritised and aligned with roadmap objectives.
• Define epics and acceptance criteria with enough clarity that engineering teams can estimate, plan, and deliver with confidence.
• Ensure delivery quality through active participation in iteration reviews, demos, and retrospectives.
• Establish and maintain a clear definition of ‘stable’ and ‘done’ for product increments, particularly for cross-hub integrations.
• Monitor delivery metrics and use data to surface risks, unblock teams, and improve predictability.

Stakeholder Engagement

• Engage directly with retailers, OEMs, financiers, and dealer group leadership to understand their reporting and insight needs, validate product direction, and gather feedback on delivered features.
• Build strong working relationships with regional stakeholders across engineering, support, professional services, sales, and data platform partners such as ThoughtSpot.
• Represent the product function in cross-functional forums, clearly articulating priorities, dependencies, and trade-offs.
• Prepare and deliver stakeholder communications (programme updates, investment cases, go-to-market briefs) that are clear, data-informed, and actionable.
• Act as the primary product point of contact for your team when interacting with data platform partners, hub product teams, and Keyloop’s commercial organisation.

Cross-Product & Platform Thinking

• Work across Keyloop’s hub reporting portfolio (Acquisition, Service, Sales, and beyond), identifying patterns, shared requirements, and opportunities for convergence or reuse across markets.
• Collaborate with other Product Managers across Keyloop to ensure coherent customer experiences across the platform ecosystem.
• Support infrastructure modernisation efforts from a product perspective — defining customer impact, rollout sequencing, and communication plans.

Skills, Know-How & Experience

Required

• 4–7 years of product management experience in B2B SaaS, enterprise software, or platform-based technology environments.
• Proven ability to own a product area end-to-end — from discovery and prioritisation through delivery and post-launch iteration.
• Strong experience working with Agile/SAFe delivery frameworks, including backlog management, PI planning, and close collaboration with the engineering team, acting as both roadmap owner and backlog owner.
• Demonstrated ability to engage enterprise customers and translate complex operational requirements into clear product specifications.
• Strong stakeholder management skills — comfortable presenting to and influencing senior leadership, commercial teams, and external partners.
• Practical experience using AI tools in product management workflows — such as LLM-based assistants for research, analysis, communication drafting, or backlog refinement. We expect candidates to demonstrate how AI enhances their productivity and decision-making today, not just awareness of AI concepts.
• Understanding of API-driven architectures, platform ecosystems, and integration patterns — you don’t need to write code, but you need to understand how systems connect and where integration complexity lives.
• Excellent written and verbal communication in English. Additional languages relevant to EMEA or GCC markets are an advantage.
• Comfortable working remotely in a distributed, cross-cultural team environment spanning multiple time zones across EMEA, GCC, and Asia-Pacific.

Preferred

• Experience with business intelligence or analytics platforms (e.g. ThoughtSpot, Tableau, Power BI, Looker) or adjacent data verticals (e.g. data pipelines, feature stores, embedded analytics).
• Familiarity with generative AI and natural-language querying products (e.g. RAG, LLM-powered chat interfaces) and how they shape product and data requirements.
• Background in or genuine curiosity about the automotive retail sector and the data that drives dealership, OEM, and financier decision-making.

What Keyloop offers