Ai engineer

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. At Ruby Labs we are looking for an AI Engineer (Strong Middle / Senior level) to own and drive the quality, reliability and evolution of our AI systems in production.

• Take ownership of major AI features and LLM workflows and deliver them to production within agreed timelines.
• Own AI output quality, structure and predictability across user-facing AI interactions, with consistent structured output across different LLMs for the same request type.
• Integrate and orchestrate multiple LLM providers through an AI gateway, managing model selection, fallback strategies and cost optimisation.
• Design and orchestrate tool-using and agentic AI workflows: clean tool contracts (including MCP-based tools), function-calling interfaces and reliable AI-to-system integrations.
• Build and maintain multi-step LLM workflows and RAG pipelines (indexing, embeddings, retrieval, re-ranking) for reasoning, context reuse and search.
• Design and manage production prompt systems with dynamic prompting, context injection, and conditional logic.
• Own prompt management, the release of LLM experiments and Langfuse-based evaluation pipelines: test datasets, LLM-as-a-judge, output scoring.
• Run A/B tests across models and prompts, analyse the results and present the data-driven impact of AI features and experiments.
• Deep-debug LLM chains using Langfuse traces: identify bottlenecks, optimise for cost, latency and context-window usage, and root-cause hallucinations and logic errors.
• Write clean, scalable and maintainable TypeScript across the Node.js / Cloudflare Workers stack.
• Build reliable backend logic for AI systems: request and output validation, error handling, fallback flows for malformed or low-quality model responses, and reliable tool execution.
• Ensure high code quality through tests (including validation and fallback paths for AI output), code reviews and clear engineering standards.
• Monitor AI system metrics, quality signals, latency and release health, and resolve production issues with a documented root cause.
• Document prompt designs, model and routing choices, evaluation results and architectural decisions, so others can pick up the work.

• 4+ years of backend/fullstack software engineering experience, with production-grade TypeScript/Node.js.
• 1+ year of AI/LLM systems in production with real users, not only side projects or experiments.
• Daily use of AI-centred development tools (Claude Code, Cursor or similar).
• Deep hands-on experience with LLM APIs (OpenAI, Anthropic, Google Gemini or similar) in production: structured output, function calling, streaming, token and cost control.
• Experience with agentic AI, multi-step orchestration, tool-based workflows (function calling / tool execution) or RAG pipelines (indexing, retrieval, re-ranking).
• Experience with LLM observability and evaluation tools (Langfuse, LangSmith or similar).
• Experience with AI gateways and model routing (OpenRouter, Cloudflare AI Gateway or equivalent).
• Solid understanding of relational databases (PostgreSQL) and caching (Redis, KV or similar).
• Exceptional ownership and personal responsibility for engineering quality and delivery.
• Будет плюсом: Evaluation frameworks (LLM-as-a-judge, RAGAS) and building test datasets; MCP (Model Context Protocol): building MCP servers/clients or designing tool contracts for AI agents; Edge/serverless runtimes (Cloudflare Workers) and their services: KV, Durable Objects, Queues, R2, Containers; Search engines and vector search (OpenSearch, Elasticsearch, pgvector), embeddings; Background workflow engines (Hatchet, Temporal, Inngest) for high-volume LLM pipelines; Browser automation and browser agents (Playwright, CDP, browser-use); Practical fine-tuning for domain-specific tasks or strict JSON/schema compliance; Working Python for data science, evaluation scripts, or AI tooling

• Embrace the freedom to work from anywhere, anytime, promoting a healthy work-life balance.
• Enjoy unlimited paid time off to recharge and prioritize your well-being, without counting days.
• Celebrate and relax on national holidays with paid time off to unwind and recharge.
• Experience seamless productivity with top-notch Apple MacBooks provided to all employees who need them.
• 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.