Senior AI Engineer

Ruby Labs is a leading tech company that creates and operates innovative consumer products across health, education, and entertainment industries. The engineering organization uses a squad-based structure, with this role operating within an AI engineering squad.

• 6+ years of backend/full-stack software engineering experience, including production-grade TypeScript/Node.js.
• Experience with Next.js and/or Python is a plus.
• 2+ years of experience building AI/LLM systems in production (less experience considered for exceptional candidates).
• Deep hands-on experience with LLM APIs such as OpenAI or Anthropic.
• Experience with Agentic AI, multi-agent orchestration, tool-based workflows, and/or RAG pipelines.
• Experience with LLM observability tools like Langfuse or LangSmith.
• Experience with AI gateways and model routing solutions such as OpenRouter.
• Solid understanding of Redis and relational databases such as PostgreSQL.
• Exceptional ownership mindset and responsibility for engineering quality and delivery.

Nice to have:

• Experience with AI-centered development tools like Cursor, Claude Code, or Windsurf.
• Familiarity with evaluation frameworks such as LLM-as-a-judge or RAGAS.
• Experience in high-pressure startup environments with rapid product iteration.
• Experience with MCP (Model Context Protocol) including building MCP servers/clients or tool contracts.
• Experience with edge and serverless runtimes like Cloudflare Workers and supporting services.
• Experience with payments, billing, and checkout flows or orchestration platforms.
• Practical experience fine-tuning models for domain-specific tasks or strict JSON/schema compliance.
• Working proficiency in Python for data science, evaluation scripts, or AI tooling.

• 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 with frameworks such as LangChain or LlamaIndex.
• Design and manage production prompt systems with dynamic prompting, context injection, and conditional logic.
• Own 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.
• Monitor AI system metrics, quality signals, latency, and release health using Langfuse and other observability tools.
• Deep-debug complex LLM chains using Langfuse traces 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 with strong error handling, request validation, fallback flows, and predictable behaviour.
• 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.

Applicants must be located within approximately ± 4 hours of CET (Central European Time) zone for optimal collaboration and communication.