Senior AI Engineer

Remote from
Europe flag
Europe
Annual salary
Undisclosed
Salary information is not provided for this position. Check our Salary Directory to estimate the average compensation for similar roles.
Employment type
Full Time,
Job posted
Apply before
10 Jul 2026
Experience level
Senior
Views / Applies
24 / 6

About Ruby Labs

Crafting Consumer Products of Tomorrow

Actively Hiring
Verified job posting
This job post has been manually reviewed for authenticity and compliance.

AI Summary

Ruby Labs seeks a Senior AI Engineer to own and drive production AI systems. This high-ownership role involves end-to-end delivery of major AI features, production stability, and data-driven experimentation using tools like Langfuse and OpenRouter. The position requires 6+ years of engineering experience with production-grade TypeScript/Node.js and 2+ years building AI/LLM systems. You will work in a squad-based structure, collaborating with product, growth, data, and billing teams. The ideal candidate has deep experience with LLM APIs, agentic AI, and multi-step workflows.

Role DNA

Job Complexity
Easy Hard
Pace & Pressure
Relaxed Fast-paced
Autonomy Level
Guided Full Ownership
Communication Load
Independent Highly Collaborative
AI Insight The role requires deep technical expertise in AI/LLM systems, production engineering, and integration with multiple teams, making it highly complex. The expectation to own features end-to-end and drive quality adds to the difficulty.

Salary Analysis

Median Market Rate
$190,000
US Market
$150k – 250k
0 $275k
AI Insight The salary is not specified in the listing, but based on US market data for Senior AI Engineers, the median is approximately $190,000. This role likely offers a competitive package, especially considering the high ownership and technical requirements.

Key Skills

TypeScript Node.js LangChain LLM APIs Agentic AI OpenRouter Langfuse Next.js Redis A/B Testing

Dear Hiring Manager,

I am writing to express my strong interest in the Senior AI Engineer position at Ruby Labs. With over 6 years of backend and full-stack engineering experience and 2+ years focused on production AI systems, I am excited about the opportunity to own and drive the quality and evolution of your AI systems. My expertise in TypeScript, Node.js, and LLM APIs aligns well with your tech stack and the high-ownership nature of this role.

In my previous role, I designed and deployed multi-step LLM workflows using LangChain and managed production prompt systems with dynamic context injection. I also have hands-on experience with agentic AI and tool-using systems, including defining clean tool contracts. I am confident I can contribute immediately to your squad-based structure and help deliver major AI features reliably.

Thank you for considering my application. I look forward to the possibility of discussing how my skills can benefit Ruby Labs.

Sincerely,
[Your Name]

Describe your experience building production-grade LLM systems. What tools and frameworks have you used, and how did you ensure reliability?
I have 2+ years building LLM systems using OpenAI and Anthropic APIs, with LangChain for orchestration. I used Langfuse for tracing and evaluation, implemented fallback strategies via OpenRouter, and built output-type-based systems to enforce structure. Reliability was ensured through extensive testing, monitoring, and prompt versioning.
How would you design a multi-step LLM workflow that involves tool-use and agentic behavior? Can you provide an example?
I would define clear tool contracts using MCP or function calling, then use a router agent to determine which tool to invoke based on user input. For example, a customer support agent could query internal databases or billing systems. I'd orchestrate with LangChain, manage context windows, and add fallbacks for errors.
How do you approach A/B testing for AI models? Describe a scenario where you compared two models or prompts. What metrics did you track?
I set up A/B tests using Langfuse's experiment features, splitting traffic between two models or prompt versions. I tracked metrics like response quality, latency, cost, and user engagement. For example, I compared GPT-4 vs Claude for summarization, analyzing accuracy and coherence.
You own a critical AI feature that is experiencing high latency and occasional hallucinations. Describe your debugging and optimization process.
First, I'd use Langfuse traces to identify bottlenecks, such as slow LLM calls or redundant context loading. I'd optimize prompt size, use caching with Redis, and implement fallback models. For hallucinations, I'd add validation steps or scoring systems to catch errors. I'd also monitor logs and set up alerts.
How do you ensure code quality and maintainability in a fast-paced environment?
I follow strict code reviews, write unit and integration tests, and enforce linting. I also document architecture decisions and refactor regularly. In a fast-paced setting, I prioritize modular design to allow independent changes and use CI/CD pipelines for safe deployments.

About us

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. Learn more about our story at: https://rubylabs.com/about-us/

About the role

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

  • 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.

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/1tzxGX4Uu7Ts_HCLFXESKLnKaaBfVCPf1f9AYZPrkjJM/preview?tab=t.0

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)

  • Second Interview (30 minutes)

  • Final Interview (20 minutes)

Life at Ruby Labs

At Ruby Labs, we move fast, aim high, and expect the same from our team. We’re not here to play small—we’re here to build, grow, and win. That means we look for people who are ambitious, driven, and ready to give their best every single day.

This is a place for individuals who thrive under pressure, embrace challenges, and see opportunity in every obstacle. If you’re hungry to achieve, motivated by impact, and want to grow at the speed of your own ambition, Ruby Labs offers the platform to make it happen.

Here, effort is matched with reward. We recognize those who go all in and deliver results, and we create space for people who want more—more responsibility, more growth, and more success.

#LI-Remote

Apply now >

Annual salary information is not provided for this position. Explore salary ranges for similar roles in our Salary Directory ›

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