At Ruby Labs we are looking for a Senior AI Engineer to own and drive the quality, reliability, and evolution of our AI systems in production.

This is a high-ownership role. You will be responsible for end-to-end delivery of major AI features, production stability of AI systems, and data-driven experimentation using tools like Langfuse, Mixpanel and OpenRouter. You’ll work in a modern stack built on Next.js, TypeScript, Node.js, and Redis, collaborating closely with product, growth, data, and billing teams. Increasingly, this includes building agentic, tool-using AI systems — defining clean tool contracts (including MCP-based tools) and orchestrating how AI interacts with internal services and business systems.

Our engineering organization uses a squad-based structure. You will operate within an AI engineering squad, contributing as a senior technical voice and driving engineering quality within your area of the product.

Key Responsibilities

AI Systems Ownership & Feature Delivery

• 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 / 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

Prompt Engineering & Experimentation

• 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 to root-cause hallucinations and logic errors

Code Quality & Production Reliability

• Write clean, scalable, and maintainable TypeScript code across the Next.js / Node.js stack

• Build reliable backend logic for AI systems, with strong error handling, request validation, fallback flows, and predictable behavior 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

Qualifications

• 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 may be considered for exceptional candidates.

• Deep hands-on experience working with LLM APIs (OpenAI, Anthropic, or similar) in production environments.

• Experience with Agentic AI, multi-agent orchestration, tool-based workflows (function calling/tool execution), and/or RAG pipelines, including indexing, retrieval, and re-ranking.

• Experience with LLM observability tools such as Langfuse, LangSmith, or similar platforms.

• Experience with AI gateways and model routing solutions, such as OpenRouter or equivalent technologies.

• Solid understanding of Redis and relational databases, such as PostgreSQL.

• Exceptional ownership mindset and personal responsibility for engineering quality and delivery.

Nice to have

• Experience with AI-centered development tools such as Cursor, Claude Code, Windsurf, or similar platforms.

• Familiarity with evaluation frameworks, including LLM-as-a-judge, RAGAS, or similar approaches.

• Experience working in high-pressure startup environments with rapid product iteration cycles.

• Experience with MCP (Model Context Protocol), including building MCP servers/clients or designing tool contracts for AI agents.

• Experience with edge and serverless runtimes, such as Cloudflare Workers, and supporting services including KV, Durable Objects, Queues, R2, and D1.

• Experience with payments, billing and checkout flows, or orchestration platforms.

• Practical experience fine-tuning models for domain-specific tasks or achieving strict JSON/schema compliance.

• Working proficiency in Python for data science, evaluation scripts, or AI tooling.

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)

• Technical Interview (60 minutes)

• Final Interview (30 minutes)