About this role.
Ruby Labs is seeking a Technical AI Product Manager to own and grow the integration and connector ecosystem supporting its direct-to-consumer AI products. The role manages roadmap prioritization for MCP servers, third-party APIs, and app integrations, with accountability for adoption, reliability, latency, cost, and business impact. This PM will work closely with AI engineers on prompts, structured outputs, agentic workflows, evaluations, and technical product specifications. The position requires strong API and analytics fluency, hands-on use of AI tools, and the ability to operate independently in a fast-paced remote environment aligned with CET hours. The role is well suited to a technically strong product leader who can make data-driven trade-offs and deliver end-to-end outcomes.
Role DNA
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Job Complexity
5/5Pace & Pressure
5/5Autonomy Level
5/5Communication Load
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Core skills
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Cover letter sample
Dear Hiring Team,
I am excited to apply for the Technical AI Product Manager role at Ruby Labs. My product-management experience combines technical API and platform work with end-to-end ownership, from customer discovery and prioritization through launch, measurement, and iteration.
I can partner closely with AI engineers on connector roadmaps, structured outputs, agentic workflows, evaluation criteria, and reliability standards while translating technical trade-offs into clear business decisions. I am comfortable using product analytics, experimentation, and AI-assisted workflows to prioritize integrations based on adoption, retention, performance, and cost.
I would welcome the opportunity to help Ruby Labs scale a reliable, high-impact connector ecosystem for its consumer AI products.
Sample interview questions
I would score candidate connectors using a weighted model covering validated user demand, expected retention or revenue impact, strategic category coverage, implementation effort, ongoing maintenance burden, security and data-access risk, and anticipated reliability. I would launch the highest-value integrations behind measurable success criteria, then use adoption, successful task completion, error rate, latency, and retention lift to decide whether to expand, improve, or retire them.
I would define an integration contract covering authentication, permissions, schema mapping, error handling, rate limits, retries, observability, versioning, and ownership. Before launch, I would require automated contract and end-to-end tests, clear acceptance criteria, fallback behavior, and dashboards for uptime, tool-call success rate, latency, and cost. Ongoing monitoring and an incident process would ensure quality does not decline as the connector catalog grows.
I would begin with the user job to be done and define the workflow, expected inputs and outputs, allowed tools, failure modes, and escalation or fallback paths. I would work with engineering to specify prompts, structured schemas, evaluation datasets, and quality thresholds, then monitor task success, user corrections, hallucination or tool-failure rates, latency, and cost after release.
I would avoid relying on a single vanity metric and instead establish a metric tree. Primary outcomes could include activated users completing connector-powered tasks and retention impact, supported by tool-call success rate, integration adoption, time to value, p95 latency, error rate, and cost per successful task. I would segment results by connector, user cohort, and acquisition channel to identify where the product is creating durable value.
I would frame the decision around differentiated user value, speed to market, total cost of ownership, security and compliance, reliability requirements, vendor concentration risk, and internal capability. Buying is appropriate when a mature solution solves a non-differentiating problem quickly; building is justified when the workflow is central to product differentiation or requires control that vendors cannot provide. I would document assumptions and revisit the decision as usage and economics evolve.
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, 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, ensuring product requirements are reflected in technical design.
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, including 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 on a regular cadence.
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 both 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.
Qualifications
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 needing everything translated.
Practical understanding of how LLMs work and what modern AI products involve — prompts, structured outputs, agents / tool use, and their 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 — this is how the team operates; it is not optional.
Strong analytical skills and hands-on proficiency with a product analytics tool (Mixpanel preferred) — 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 both 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.
Location
Ruby Labs operates within the CET (Central European Time) zone. Applicants from any country are welcome to apply for the position as long as they are located within approximately ± 4 hours of CET. This ensures optimal collaboration and communication during working hours.
Benefits
Discover the perks of being part of our vibrant team! We offer:
Remote Work Environment: Embrace the freedom to work from anywhere, anytime, promoting a healthy work-life balance.
Unlimited PTO: Enjoy unlimited paid time off to recharge and prioritize your well-being, without counting days.
Paid National Holidays: Celebrate and relax on national holidays with paid time off to unwind and recharge.
Company-provided MacBook: Experience seamless productivity with top-notch Apple MacBooks provided to all employees who need them.
Flexible Independent Contractor Agreement: Unlock the benefits of flexibility, autonomy, and entrepreneurial opportunities. Benefit from tax advantages, networking opportunities, reduced employment obligations, and the freedom to work from anywhere. Read more about it here: https://docs.google.com/document/d/1nkrN76JlZkbKj9WSOhlT1_mni_CZeDkHdwfIjPXVwvk/preview?tab=t.0#heading=h.ndsdl4wapxtt
Be part of our fast-growing team and seize this excellent opportunity for personal and professional growth!
Interview Process
After submitting your application, we conduct a thorough review which typically takes 3 to 5 days, but may occasionally take longer due to the volume of applications received. If we see a potential fit, we proceed with the following steps:
Recruiter Screening (40 minutes)
Technical Interview (60 minutes)
Second Interview (45 minutes)
Final Interview (30 minutes)
Life at Ruby Labs
At Ruby Labs, we move fast, aim high, and expect the same from our team. We’re not here to play small—we’re here to build, grow, and win. That means we look for people who are ambitious, driven, and ready to give their best every single day.
This is a place for individuals who thrive under pressure, embrace challenges, and see opportunity in every obstacle. If you’re hungry to achieve, motivated by impact, and want to grow at the speed of your own ambition, Ruby Labs offers the platform to make it happen.
Here, effort is matched with reward. We recognize those who go all in and deliver results, and we create space for people who want more—more responsibility, more growth, and more success.
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