> Markdown version of [/jobs/ext/2686568-senior-ai-engineer](https://www.wearedevelopers.com/jobs/ext/2686568-senior-ai-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior AI Engineer - **Company:** Jobgether - **Location:** Netherlands (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** JavaScript (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Algorithm Design, Amazon Web Services, Microsoft Azure, Cloud Computing, Distributed Systems, Python (Programming Language), Node.Js, Search Technologies, Software Engineering, Systems Integration, TypeScript, Web Applications, AI Infrastructure, Large Language Models, Multi-Agent Systems, Backend, AngularJS, Low Latency, Front End Software Development, Docker - **Published:** September 3, 2026 - **Apply:** https://www.adzuna.nl/details/5867264858 ## About the Role * Demonstrated hands-on experience building and successfully shipping LLM-powered features or applications into production. * Practical experience with technologies and patterns such as RAG, embeddings, vector search, agentic systems, LLM APIs, orchestration, and tool calling. * Strong understanding of production LLM considerations, including evaluation, observability, failure modes, latency, reliability, and cost management. * Experience improving AI features based on telemetry, evaluation results, production behavior, or user feedback. * Strong software engineering background with experience designing APIs, backend services, and production-grade distributed systems. * Full-stack development experience with technologies such as Angular, JavaScript/TypeScript, Python, Node.js, or comparable technologies is a strong advantage. * Ability to write clean, maintainable, well-structured code and take ownership of solutions from implementation through production. * Willingness and ability to contribute across backend services, AI infrastructure, and user-facing product functionality. * Experience working with AWS or comparable cloud infrastructure, CI/CD pipelines, and production environments. * Strong product mindset with a bias toward shipping, rapid iteration, pragmatic problem-solving, and measurable outcomes. * Comfortable working in an environment characterized by ambiguity, rapid change, and evolving requirements. * Strong communication and collaboration skills, with the ability to work effectively with Product, ML, and Engineering teams. * Ability to challenge requirements constructively, communicate technical trade-offs, and translate AI complexity into practical product solutions. * A maintainability- and reuse-oriented mindset, with a focus on building production systems rather than isolated demonstrations. * Experience with multi-agent systems, MCP, guardrails, moderation, safety checks, prompt and context management, routing, caching, or fallback strategies is a plus. * Experience with Docker and cloud platforms such as AWS, GCP, or Azure is beneficial. * Experience with modern frontend development and customer-facing web applications is an advantage. * This role is focused on applied AI engineering rather than heavy model training, academic research, custom ML algorithm development, or theoretical optimization work. ## Description This is a hands-on engineering opportunity focused on bringing AI-powered capabilities into real-world products and production workflows. You will design, build, deploy, and continuously improve LLM-powered features within a large-scale technology environment. The role combines strong software engineering with practical expertise in RAG, embeddings, agents, tool calling, and AI orchestration. You will work closely with Product, ML, and Engineering teams to turn complex business challenges into pragmatic and scalable AI solutions. Beyond implementation, you will help establish robust evaluation, observability, monitoring, and feedback practices for production AI systems. The environment is fast-moving and product-focused, offering significant ownership and opportunities to experiment, iterate, and ship. This role is particularly suited to an engineer who enjoys taking AI capabilities from prototype through reliable, maintainable production systems. Accountabilities: * Architect, develop, deploy, and maintain production-grade LLM capabilities integrated into customer-facing products and internal workflows. * Build backend services, APIs, integrations, and supporting infrastructure that connect AI capabilities with product functionality. * Contribute to full-stack and user-facing development where required, helping deliver complete AI-powered product experiences. * Implement production-ready patterns involving LLMs, RAG, embeddings, vector search, agents, and tool calling. * Design reusable components, abstractions, and engineering patterns that improve development velocity, consistency, and maintainability. * Establish and improve evaluation frameworks, observability, monitoring, and feedback loops for AI-powered features. * Monitor and optimize AI systems for quality, latency, reliability, scalability, and inference cost. * Investigate production issues, analyze telemetry, and continuously improve AI functionality based on system performance and user feedback. * Collaborate closely with Product, ML, and Engineering stakeholders to translate product challenges into practical AI solutions. * Rapidly prototype and validate new ideas, then transform successful experiments into robust and maintainable production systems. * Contribute to engineering decisions around architecture, trade-offs, scalability, and long-term technical sustainability. ## Related Videos - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [Stop using Node.js like in 2020! What changed and what you can do today with Node.js](https://www.wearedevelopers.com/videos/100011-stop-using-node-js-like-in-2020-what-changed-and-what-you-can-do-today-with-node-js) - [How to Avoid LLM Pitfalls - Mete Atamel and Guillaume Laforge](https://www.wearedevelopers.com/videos/1328-how-to-avoid-llm-pitfalls-mete-atamel-and-guillaume-laforge) - [Building AI Applications with LangChain and Node.js](https://www.wearedevelopers.com/videos/1512-building-ai-applications-with-langchain-and-node-js) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it)