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Ruby Labs

Develops consumer health, edtech, entertainment apps

AI Engineer

AI Application EngineeringPosted on Nov 13
Full-timeNo salary listed

About the Job

Requirements

  • At least 4 years of backend or full-stack software engineering experience, including production-grade TypeScript and Node.js.
  • At least 1 year of production experience with AI or LLM systems used by real users.
  • Daily use of AI-centered development tools such as Claude Code or Cursor.
  • Hands-on production experience with LLM APIs, including structured output, function calling, streaming, and token and cost control.
  • Experience with agentic AI, multi-step orchestration, tool-based workflows, or RAG pipelines.
  • Experience with LLM observability and evaluation tools such as Langfuse or LangSmith.
  • Experience with AI gateways and model routing such as OpenRouter or Cloudflare AI Gateway.
  • Solid understanding of relational databases such as PostgreSQL and caching such as Redis or KV.
  • Strong ownership and personal responsibility for engineering quality and delivery.

Responsibilities

  • Take ownership of major AI features and LLM workflows and deliver them to production within agreed timelines.
  • Own the quality, structure, and predictability of AI outputs across user-facing interactions, ensuring 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 optimization.
  • Design and orchestrate tool-using and agentic AI workflows, including clean tool contracts, MCP-based tools, function-calling interfaces, and reliable AI-to-system integrations.
  • Build and maintain multi-step LLM workflows and RAG pipelines for indexing, embeddings, retrieval, and re-ranking.
  • Design and manage production prompt systems with dynamic prompting, context injection, and conditional logic.
  • Own prompt management, LLM experiment releases, and Langfuse-based evaluation pipelines, including test datasets, LLM-as-a-judge, and output scoring.
  • Run A/B tests across models and prompts, analyze results, and present the data-driven impact of AI features and experiments.
  • Debug LLM chains using Langfuse traces, identify bottlenecks, optimize cost, latency, and context-window usage, and find root causes of hallucinations and logic errors.
  • Write clean, scalable, and maintainable TypeScript across the Node.js and Cloudflare Workers stack.
  • Build reliable backend logic for AI systems, including request and output validation, error handling, fallback flows for malformed or low-quality model responses, and reliable tool execution.
  • Maintain 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.

Desired Qualifications

  • Experience with evaluation frameworks such as LLM-as-a-judge or RAGAS, and building test datasets.
  • Experience building MCP servers or clients, or designing tool contracts for AI agents.
  • Experience with edge or serverless runtimes such as Cloudflare Workers and related services, including KV, Durable Objects, Queues, R2, and Containers.
  • Experience with search engines and vector search such as OpenSearch, Elasticsearch, or pgvector, and embeddings.
  • Experience with background workflow engines such as Hatchet, Temporal, or Inngest for high-volume LLM pipelines.
  • Experience with browser automation and browser agents such as Playwright, CDP, or browser-use.
  • Practical fine-tuning for domain-specific tasks or strict JSON or schema compliance.
  • Working knowledge of Python for data science, evaluation scripts, or AI tooling.

About the Company

Ruby Labs

Develops consumer health, edtech, entertainment apps

Ruby Labs creates and runs a collection of consumer-facing digital products in health, education, and entertainment. Its apps are built for mobile devices and marketed directly to users, generating revenue from in-app purchases and subscriptions within its own product ecosystem. The company distinguishes itself by managing its own multi-vertical portfolio and operating with a remote-first culture, focusing on broad consumer appeal across wellness, learning, and entertainment needs. The company’s goal is to provide accessible digital platforms that help people improve well-being, acquire new skills, and enjoy engaging entertainment through its direct-to-consumer apps.

Company size
51-200
Company stage
Not listed
Total funding
Not listed
Headquarters
London, United Kingdom
Founded
2018

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