Why this role
At Rollo.ai, AI isn't a slide in a pitch deck: it runs in production and takes real work off real people's plates. As an AI Engineer, you design, build, and ship AI agents that automate complex workflows, enable better decisions, and deliver measurable ROI for our B2B clients. You work end to end: from understanding business problems to deploying, monitoring, and improving agents that are actually used.
About Rollo
Rollo.ai is Antwerp's no-nonsense AI agency. We build custom AI agents that bulldoze busywork so teams can focus on what really matters. Our team is a tight mix of engineers and strategists who turn ambitious ideas into reliable systems. We're obsessed with impact, allergic to fluff, and believe the best tech gets built by people who are curious, honest, and unafraid to push boundaries.
What you'll do
- Design & build AI solutions that automate and improve real business processes using LLMs and other ML models.
- Translate problems into agents: work with cross-functional teams and clients to spot opportunities and turn them into AI-driven solutions.
- Build and maintain scalable ML/LLM pipelines and workflows with frameworks like LangChain, LangGraph, or similar.
- Work deeply with LLMs: fine-tune, adapt, and orchestrate Large Language Models for specific client needs.
- Implement generative AI use cases: from GPT-style assistants to domain-specific agents.
- Optimize performance, scalability, latency, and cost of existing generative AI models and pipelines.
- Write clear documentation and explain solutions to both technical and non-technical stakeholders.
- Share best practices, mentor teammates, and help raise our collective bar on generative AI.
Skills & Experience
- Master's in Computer Science, Artificial Intelligence, or a related field (PhD is a plus, not a must).
- Solid understanding of Generative AI, machine learning algorithms, and deep learning (transformer-based models).
- Experience with data preprocessing, feature engineering, and model evaluation.
- Strong Python skills and hands-on experience with ML frameworks like TensorFlow, PyTorch, or Keras.
- Experience with RAG (Retrieval-Augmented Generation) workflows, tools, and platforms.
- Good understanding of data structures, algorithms, and software engineering principles.
- Comfortable working with cloud platforms (Azure, AWS, ...) and modern development practices.
Nice-to-haves
- Experience with LangChain, LangGraph, or similar LLM orchestration frameworks.
- Familiarity with MLOps practices and tools (model deployment, monitoring, CI/CD for ML).
- Experience in agile environments and managing software projects.