Ruby Labs
AI
TechnicalAIProductManager
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Technical AI Product Manager at Ruby Labs. Skills: AI Product Management, Connector Ecosystem, API Integrations, LLM Features. Own and drive roadmap for scaling connector ecosystem. Prioritize integrations and connectors”
What You'll Achieve.
Scale connectors; Grow number of integrations; Grow quality of integrations; Grow reliability of integrations; Measure success in outcomes; Deliver initiatives on time; Improve AI performance; Improve connector performance
Industry & Context.
Data-driven decision making; Pragmatic build-versus-buy decisions; Quantitative results analysis; Problem-solving
Located within +/- 4 hours of CET
What They're Looking For.
Must Have
4+ years product management, Technical platform/API/integration products, End-to-end product ownership, Read API documentation, Understand data schemas and JSON, Partner with engineers, Understand how LLMs work, Understand prompts, structured outputs, agents, Understand LLM limitations, Working familiarity with MCP, Working familiarity with connectors, Working familiarity with integration products, Working familiarity with developer-platform products, Hands-on daily use of AI tools, Product analytics tool proficiency, Mixpanel proficiency preferred, Excellent communication skills, Excellent stakeholder-management skills, Comfort in remote, asynchronous environment
Nice to Have
Direct MCP experience, Experience growing integrations marketplace, Experience scaling connector ecosystem, Experience with AI gateways, Experience with model routing, Experience with LLM observability, Experience with LLM evaluation tooling, Familiarity with TypeScript ecosystem, Familiarity with Node.js ecosystem, Familiarity with Next.js ecosystem, Experience in startup environment, Experience in fast-paced environment, Experience in high-iteration product environment
What You'll Do.
Own and drive roadmap for scaling connector ecosystem
Prioritize integrations and connectors
Write product specifications
Write acceptance criteria
Define framework for evaluating connectors
Define framework for onboarding connectors
Define framework for monitoring connectors
Define framework for maintaining connectors
Translate AI capabilities into product requirements
Partner with AI engineering team
Make build versus buy decisions
Define scope of integration infrastructure
Own features end-to-end
Define success metrics for connectors
Define success metrics for AI features
Design and run experiments
Design and run A/B tests
Build and maintain dashboards
Use observability tools
Monitor AI performance
Monitor connector performance
Surface actionable insights
Surface recommendations
Own and prioritize integrations backlog
Collaborate with AI engineering
Collaborate with growth teams
Collaborate with data teams
Collaborate with billing teams
Deliver initiatives reliably
Communicate technical trade-offs
Communicate priorities
Communicate roadmap decisions
Use AI tools for prototyping
Use AI tools for specification writing
Use AI tools for analysis
Use AI tools for problem-solving
How You'll Work.
Team & Collaboration
AI engineering squad; Cross-functional teams; Product teams; Growth teams; Data teams; Billing teams; Technical stakeholders; Non-technical stakeholders
Communication Scope
Clear product specifications; Clear technical trade-offs; Clear priorities; Clear roadmap decisions
Process & Methodology
Roadmap, Backlog prioritization, End-to-end ownership
Full Job Description
ABOUT US Ruby Labs is a leading tech company that creates and operates innovative consumer products. We offer a diverse range of opportunities across the health, education, and entertainment industries. Our innovative teams are driving the future of consumer-led products, and we're always looking for passionate individuals to join us. Learn more about our story at: https://rubylabs.com/about-us/ ABOUT THE ROLE At Ruby Labs, we are building Direct-to-Consumer products in the AI category. We’re looking for a Technical AI Product Manager to own and scale the integrations and connector ecosystem that powers our AI features — the third-party APIs, app integrations, and MCP (Model Context Protocol) servers that let our products reach beyond the model itself. This is a high-ownership, technical role. Your core mandate is to scale connectors — growing the number, quality, and reliability of integrations available to our users — while making data-driven decisions about what to build, in what order, and how to measure success. You’ll operate inside an AI engineering squad, working shoulder-to-shoulder with engineers on prompt systems, structured outputs, agentic workflows, and evaluation, and collaborating closely with product, growth, data, and billing teams. We’re looking for someone technical enough to read API docs and talk to engineers without a translator, who treats AI tools as a core part of their daily workflow, and who measures success in outcomes — not effort. KEY RESPONSIBILITIES - 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) that power AI features. - 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, monitori
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