Technical AI Product Manager

Ruby Labs is a leading tech company that creates and operates innovative consumer products across the health, education, and entertainment industries. They focus on building Direct-to-Consumer products in the AI category.

• 4+ years in product management with strong experience in technical, platform, API, or integration products.
• Demonstrated end-to-end product ownership from hypothesis to iteration.
• Solid technical fluency reading API documentation, understanding data schemas and JSON.
• Practical understanding of LLM workings and AI product features including prompts, structured outputs, and agent/tool use.
• Familiarity with MCP (Model Context Protocol), connectors, or integration/developer-platform products.
• Daily hands-on use of AI tools like Claude.
• Strong analytical skills with proficiency in product analytics tools, preferably Mixpanel.
• Excellent communication and stakeholder management in a remote, asynchronous environment.

Nice to have:

• Hands-on experience building or integrating MCP servers or clients.
• Experience growing integrations marketplaces or connector ecosystems.
• Experience with AI gateways/model routing tools such as OpenRouter and LLM observability tools like Langfuse or LangSmith.
• Familiarity with the TypeScript / Node.js / Next.js ecosystem.
• Experience in startup or fast-paced, high-iteration product environments.

• Own and drive the roadmap for scaling the connector ecosystem, including MCP servers, third-party APIs, and app integrations.
• Prioritise integrations based on user demand, business impact, and engineering effort.
• Write clear product specifications and acceptance criteria, collaborating with AI engineers.
• Define and manage frameworks for evaluating, onboarding, monitoring, and maintaining connectors.
• Translate AI capabilities, such as LLM features, agentic workflows, and tool use, into product requirements.
• Partner with AI engineering on prompt systems, structured outputs, and evaluation pipelines.
• Make build-versus-buy decisions and define the integration infrastructure scope.
• Own features end-to-end from discovery to post-launch iteration.
• Define success metrics including adoption, reliability, latency, cost, retention, and engagement.
• Design and run experiments and A/B tests to inform decisions.
• Build and maintain dashboards in Mixpanel and use observability tools like Langfuse.
• Provide actionable insights to engineering and leadership teams regularly.
• Own and prioritise the integrations product backlog.
• Collaborate closely with cross-functional teams to deliver initiatives on time.
• Communicate technical trade-offs and roadmap decisions clearly to stakeholders.
• Use AI tools such as Claude daily for prototyping, specification, analysis, and problem-solving.

Applicants must be located within approximately ±4 hours of the CET (Central European Time) zone to ensure optimal collaboration during working hours.