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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # SAGACIFY - AI Systems Engineer - **Company:** BETUNED BV - **Location:** Antwerpen, Belgium - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Automation of Tests, DevOps, Machine Learning, Open Source Technology, Management of Software Versions, Large Language Models, AI Platforms, Low Latency, Machine Learning Operations - **Published:** September 1, 2026 - **Apply:** https://europa.eu/eures/portal/jv-se/jv-details/MDM0NWU2Y2QtYTYxOS00ZjE0LTg3NWEtY2RhMGQ5ZDM1OWEwIDM?lang=en ## About the Role We're on the lookout for a Mid-Level AI Systems Engineer who bridges AI engineering and MLOps. Someone who loves getting hands-on with LLMs, agents, and RAG pipelines, and who cares just as much about what happens once a model reaches production as about building it in the first place. In this role, you'll design, build, deploy, and operate production-grade AI systems, with a strong focus on generative AI, LLM-based applications, and reliable machine learning operations. In practice your time is split roughly between 60-70% AI Engineering and 30-40% MLOps., * You have 3 to 5 years of experience in AI/ML engineering or related fields * You have a solid understanding of LLM fundamentals: Transformers, attention mechanisms, generation parameters and fine-tuning approaches * You have strong problem-solving ability and algorithmic creativity * You communicate clearly with both technical and non-technical stakeholders * You have a team spirit and enjoy collaborating across multiple roles * You bring rigour, responsiveness and a good incident-handling mindset * You're autonomous, curious, and quick to learn new tools * You can communicate fluently in Dutch, English and French, or at least the first two languages Don't worry if you don't tick every single box, what matters most is the right mindset and a drive to learn. If you think we're a match, we'd love to hear from you. You'll be part of a team of enthusiasts who love to learn and continuously develop skills in different areas and technologies. You'll work with both the Sagacify and Craftzing teams, purposefully driven to create solutions that make a lasting difference, in an environment tailored to your needs. ## Description In this role you sit at the intersection of engineering and operations, working across teams and disciplines. You'll report to the Head of ML at Sagacify and collaborate with the wider Sagacify and Craftzing delivery organisation. A role that can naturally grow towards a Team Lead position over time., * Orchestrate AI system components: LLMs, vector databases, APIs, orchestration layers, and user interfaces * Develop autonomous agents and conversational systems that can plan actions and interact with external tools or APIs * Build and optimise RAG pipelines connecting enterprise data sources to LLMs for grounded, contextualised, reliable answers * Evaluate system quality through generative AI metrics, coherence tests, and production monitoring (latency, API costs, bias) * Deploy and scale solutions with strong attention to latency, security, reliability and cost efficiency * Keep an eye on the ecosystem for new models, frameworks and techniques, including open-source tools such as LangChain, LangGraph, Langfuse, etc. * Perform prompt and context engineering to improve output quality, reduce hallucinations, and manage conversational state effectively MLOps (30-40%) * Build and maintain automation for model deployment, including CI/CD pipelines and automated testing * Continuously monitor model performance in production, including drift detection and quality metric tracking * Manage updates of libraries, models, and related dependencies in production environments * Ensure versioning, reproducibility and safe rollout of models and AI services * Collaborate closely with ML engineers, developers, DevOps and infrastructure teams for smooth delivery * Stay current with the latest MLOps practices, tools and platform components ## Related Videos - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Swapping Low Latency Data Storage Under High Load](https://www.wearedevelopers.com/videos/746-swapping-low-latency-data-storage-under-high-load) - [This App Reached 10,000 Users in One Week. Here's How.](https://www.wearedevelopers.com/videos/100329-this-app-reached-10-000-users-in-one-week-here-s-how) - [AI, DEI & Community: What’s Next for Talent Acquisition in 2025?](https://www.wearedevelopers.com/videos/1315-ai-dei-community-what-s-next-for-talent-acquisition-in-2025) - [DevOps Maturity Check – a way to balance autonomy and alignment](https://www.wearedevelopers.com/videos/58-devops-maturity-check-a-way-to-balance-autonomy-and-alignment) - [Engineering Mindset in the Age of AI - Gunnar Grosch, AWS](https://www.wearedevelopers.com/videos/1735-engineering-mindset-in-the-age-of-ai-gunnar-grosch-aws) ## Related Articles - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers)