AI Engineer

About the role

About RevoData RevoData is a boutique Data & AI consultancy and proud Databricks Gold partner. We focus exclusively on Databricks, allowing us to go deep and do things properly. We help companies across Europe unlock the value in their data, helping them design and build scalable platforms that support real business use cases. We foster a no-ego, no nonsense culture where collaboration, proactivity and knowledge sharing are part of everyday work. Sound like your kind of environment? Then keep scrolling! You are a builder who thrives as much in the first as in the last mile of AI - the space between a cool demo and a robust, production-ready system. You enjoy turning AI capabilities into real-world applications that people actually use, and you don't just ship a working prototype; you can prove it works, then make it measurably better. As an AI Engineer at RevoData, you embed with clients to design and build AI solutions that solve real business problems. You combine strong technical skills with curiosity and pragmatism, and you enjoy bridging the gap between experimentation and production. We'd love to talk if: You've built AI systems that run in the real world: You have experience across the full lifecycle - from early experimentation to deployment and monitoring - and understand what it takes to make AI systems reliable in production. You're experienced with LLMs & GenAI: You've moved beyond simple prompts and have built production-grade GenAI applications, including RAG architectures, agentic workflows, and fine-tuning, using platforms like OpenAI, Anthropic, Azure AI, or similar. You're comfortable with GenAI frameworks: You've used tools like LangChain, LangGraph, Pydantic AI, Hugging Face, or DSPy, and understand how to structure and orchestrate AI-driven applications beyond simple prototypes. You're evaluation-driven: You don't trust "it seems better." You establish a baseline, define metrics that actually capture the failure modes that matter, and iterate against them - so you can show with numbers that a change to a prompt, retrieval step, model, or parameter genuinely moved the needle. You understand LLMOps & MLOps: You understand that AI is only as good as its lifecycle management. You're comfortable with experiment tracking, model versioning, observability, and deployment (e.g. MLflow or comparable tooling), and you know how to build automated pipelines that handle monitoring, evaluation, and CI/CD for both traditional ML and LLMs. You can work with data and build scalable pipelines: You've worked with data in real environments and understand how to design training and inference pipelines that scale with usage and complexity - and work reliably in production. You're a pragmatic Python Engineer: You have extensive experience with Python and its data/ML libraries, and you write clean, testable, well-structured code. You favour focused, self-contained solutions over sprawling ones, and you know what not to build under real-world time and budget constraints. You're comfortable working in the cloud: You've deployed or worked with AI solutions in environments such as AWS, Azure or GCP, and understand the basics of building and running systems there. You have a Consultant Mindset: You enjoy being client-facing. You don't just execute; you advise. You can translate a vague business challenge into a technical roadmap and lead a project from scoping to delivery. You can explain the "why" behind an architecture to a CTO while pair-programming with an engineer to debug a pipeline. Nice to haves: Experience with Databricks (or a Databricks certification - e.g. ML Engineer or GenAI Engineer) Experience with deep learning frameworks (PyTorch, TensorFlow) Experience with LLMOps tooling in production environments (evaluation, monitoring, drift detection) Dutch proficiency No Databricks experience? No problem - we'll teach you. We focus exclusively on Databricks, so you'll be working with your hands deep in the Databricks Data Intelligence Platform: PySpark, SQL, Delta Lake, Unity Catalog, MLflow, and the latest Mosaic AI features. But we don't expect you to walk in as a power user. If you've got strong AI engineering skills and extensive experience with comparable tooling - that's enough to get started. For candidates without Databricks experience who want to ramp up quickly, we're willing to invest. We offer a 7 month crash course covering certifications, hands-on client project work, and an internal knowledge-sharing session to cement what you've learned. This track transitions to a permanent contract upon reaching the agreed milestones. It's designed to get you up to speed fast, with full support from the team along the way! This role is open from Medior to Principal level candidates. Salary details are in the Additional Info section below. Tech Playground: Love experimenting? So do we. Play around with Databricks, Terraform, Terragrunt, Asset Bundles, CI/CD, monitoring & alerting tools, Cursor and more. Unli

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