Technical AI Product Manager

Ruby Labs is a leading tech company that creates and operates innovative consumer products across health, education, and entertainment industries.

• 4+ years in product management with a strong track record on technical, platform, API, or integration products.
• Demonstrated end-to-end ownership of products from hypothesis through production and iteration.
• Solid technical fluency: comfortable reading API documentation, understanding data schemas and JSON, and partnering with engineers without translation.
• Practical understanding of how LLMs work and what modern AI products involve, including prompts, structured outputs, agents/tool use, and limitations.
• Working familiarity with the concepts behind MCP (Model Context Protocol), connectors, or integration/developer-platform products.
• Hands-on daily use of AI tools (Claude or similar) for real work.
• Strong analytical skills and hands-on proficiency with a product analytics tool (Mixpanel preferred) involving funnels, cohorts, and dashboards.
• Excellent communication and stakeholder-management skills with comfort in a remote, asynchronous environment.

Nice to have:

• Direct hands-on experience with MCP—building, integrating, or shipping MCP servers or clients.
• Experience growing an integrations marketplace or connector ecosystem, scaling the breadth and reliability of third-party integrations.
• Experience with AI gateways/model routing (OpenRouter or similar) and LLM observability/evaluation tooling (Langfuse, LangSmith).
• Familiarity with the TypeScript / Node.js / Next.js ecosystem.
• Experience in a startup or fast-paced, high-iteration product environment.

• Own and drive the roadmap for scaling the connector ecosystem, including the number, quality, and reliability of integrations (MCP servers, third-party APIs, and app integrations).
• Prioritise integrations and connectors based on user demand, business impact, and engineering effort.
• Write clear product specifications and acceptance criteria for new connectors, working closely with AI engineers.
• Define and own the framework for evaluating, onboarding, monitoring, and maintaining connectors over time.
• Translate AI capabilities, including LLM features, agentic workflows, and tool use, into clear, buildable product requirements.
• Partner with the AI engineering team on prompt systems, structured outputs, and evaluation pipelines.
• Make pragmatic build-versus-buy decisions and define the scope of integration infrastructure.
• Own features end-to-end from discovery and specification through QA, launch, and post-launch iteration.
• Define success metrics for connectors and AI features such as adoption, reliability, latency, cost, retention, and engagement impact.
• Design and run experiments and A/B tests, making ship, iterate, or kill decisions based on quantitative results.
• Build and maintain dashboards in Mixpanel and use observability tools such as Langfuse to monitor AI and connector performance and health.
• Surface actionable insights and recommendations to engineering and leadership teams regularly.
• Own and prioritise the integrations product backlog.
• Collaborate closely with AI engineering, growth, data, and billing teams to deliver initiatives reliably and on time.
• Communicate technical trade-offs, priorities, and roadmap decisions clearly to technical and non-technical stakeholders.
• Use AI tools (Claude and others) as a core part of the daily workflow for prototyping, specification writing, analysis, and problem-solving.

Ruby Labs operates within the CET (Central European Time) zone. Applicants must be located within approximately ± 4 hours of CET for optimal collaboration and communication during working hours.