Ruby Labs

Product Manager

• 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.

Technical AI Product Manager

Full-stack Engineer

• Take complete ownership and deliver major AI engineering features within agreed timelines.
• Own AI output quality, structure, and predictability across all user-facing AI interactions.
• Design, implement, and maintain output-type-based AI systems, including segmentation, routing, and enforcement.
• Ensure consistent output structure and formatting across different LLMs for the same request type.
• Integrate and orchestrate multiple LLM providers via OpenRouter, managing model selection, fallback strategies, and cost optimisations.
• Design and orchestrate tool-using and agentic AI workflows, defining clean tool contracts (including MCP-based tools), function-calling interfaces, and reliable AI-to-system integrations.
• Build and maintain complex, multi-step LLM workflows, including with orchestration frameworks such as LangChain or LlamaIndex, for advanced reasoning, context reuse, and retrieval.
• Design and manage production prompt systems with dynamic prompting, context injection, and conditional logic.
• Own the deployment and release of LLM experiments, prompt management, and Langfuse-based evaluation pipelines.
• Run A/B tests across models, analyse results, and present data-driven impact assessments of AI features and experiments.
• Monitor AI system metrics, quality signals, latency, and release health using Langfuse and other observability tools.
• Deep-debug complex LLM chains using Langfuse traces, identifying bottlenecks and optimising for cost, latency, and context-window usage, and build output-scoring systems to root-cause hallucinations and logic errors.
• Write clean, scalable, and maintainable TypeScript code across the Next.js and Node.js stack.
• Build reliable backend logic for AI systems, with strong error handling, request validation, fallback flows, and predictable behaviour in production, including reliable tool execution and AI-to-service integrations.
• Ensure high code quality through testing, code reviews, and clear engineering standards.
• Monitor, troubleshoot, and improve production performance, reliability, and system health.
• Drive maintainability and technical quality through solid architecture, refactoring, and disciplined release practices.

Senior AI Software Engineer

AI Engineer

Senior AI Engineer

QA Engineer

• Experiment Validation: Own end-to-end QA validation of experiments from preview environments through production release.
• Variant Testing: Validate all experiment variants (A/B/C/etc.) and ensure expected behavior across different user scenarios.
• Targeting & Triggers: Verify audience targeting logic, eligibility rules, and experiment trigger conditions.
• Analytics Validation: Ensure analytics events, conversions, and experiment metrics are correctly tracked and reported.
• User Flow Testing: Validate experiment behavior throughout the entire user journey.
• UI/UX Validation: Ensure experiment implementations meet design requirements and provide a consistent user experience.
• Production Monitoring: Perform post-release validation using production environments and session replay tools.
• Edge Case Detection: Identify unexpected behaviors and issues beyond predefined test cases.
• Regression Prevention: Ensure experiments do not negatively impact core product functionality.
• QA Sign-Off: Provide clear release recommendations and final QA approval before launch.

• Implement AI-powered product features and workflows based on specifications from senior engineers.
• Write, iterate on, and manage production prompt templates following established patterns for dynamic prompting and context injection.
• Participate in prompt experimentation workflows by drafting variants, running A/B tests across models via OpenRouter, and documenting results.
• Integrate structured output schemas (JSON mode, function calling, Zod/JSON schemas) to ensure AI responses are predictable and application-ready.
• Build and maintain output enforcement mechanisms such as validators and repair loops under senior guidance.
• Help implement tool calling and function calling integrations so AI features can fetch data or trigger actions, following patterns established by senior engineers.
• Contribute to evaluation pipelines and help assess prompt and model quality using Langfuse.
• Write clean, maintainable TypeScript code within the Next.js and Node.js stack.
• Participate in code reviews and incorporate feedback.
• Document technical decisions and system behaviour to support knowledge sharing.
• Collaborate with product, growth, data, and billing teams to deliver features on time.

Junior AI Engineer

AI Engineer, Junior

Customer Support

• Handle routine customer support tickets efficiently and professionally.
• Assist with ticket triage and processing to ensure timely resolution.
• Escalate complex issues to senior team members or relevant internal teams when necessary.
• Work towards achieving the set Key Performance Indicators and Service Level Agreements.
• Strive to provide accurate and friendly first-contact support to customers.
• Gather basic customer feedback to help improve our products and services.
• Assist in handling billing queries under guidance when required.

Junior Customer Support Representative – Tickets

Backend Engineer

• Participate in the solution development and maintenance of high-performance backend services and applications using Golang.
• Architect, implement, and optimize microservices-based applications, ensuring scalability, reliability, and maintainability.
• Collaborate with the DevOps team to deploy and manage Golang applications in Kubernetes clusters using Helm for efficient package management.
• Design and optimize database schemas, queries, and transactions, specifically using Postgres.
• Develop and enhance the billing system to ensure accurate and timely processing of financial transactions.
• Conduct code reviews to ensure code quality, best practices, and adherence to coding standards.
• Collaborate within the cross-functional team, including DevOps, Backend and Frontend developers, QA and product management to understand requirements and deliver high-quality software solutions.
• Maintain comprehensive documentation for code, architecture, and processes to facilitate knowledge transfer and onboarding of team members.
• Ensure decent Unit test coverage of the applications and participate in keeping the autotest suite up-to-date.

Golang Developer

• Deliver new backend features with a focus on scalability, performance, and reliability.
• Maintain, optimize, and improve existing services and infrastructure.
• Design, deploy, and operate backend services across AWS, Cloudflare, and other environments.
• Implement and evolve monitoring and observability using tools such as Sentry, OpenTelemetry (OTel), logging, alerting, and related platforms.
• Investigate and resolve production issues across distributed systems.
• Write clean, maintainable code aligned with SOLID principles, system design, and backend best practices.
• Lead incident investigations, root cause analysis, and system reliability improvements.
• Contribute to architectural decisions, documentation, and infrastructure planning.
• Collaborate with high standards for communication, ownership, and delivery.

Senior Backend Engineer

• Build, ship, and iterate on core product features across the stack.
• Take ownership of features assigned to you — from implementation through production rollout and iteration.
• Implement responsive, accessible UIs using TypeScript, TailwindCSS, and established design systems.
• Work with backend services and APIs, integrating frontend logic with scalable systems.
• Participate actively in code reviews and contribute to maintaining high engineering standards.
• Debug, optimize, and improve production systems in a high-traffic environment.
• Communicate blockers, risks, and progress early and clearly.
• Work closely with Product and the rest of the engineering team to support fast, iterative delivery.

Middle Full-Stack Engineer

Product Designer

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