AI Engineer

Are you curious about AI and ready to move beyond research - building robust, production-ready solutions that tackle real challenges in Climate Tech? At Enjins, we bring a Software Engineering mindset to everything from traditional ML models to modern LLMs and Agentic architectures. We value freedom to work with the latest technologies while creating genuine, measurable business value. About us 🚀 Since 2018, we've been engineering AI systems designed to deliver long-term, meaningful value. Operating from Utrecht and Berlin, we partner with innovative tech companies across Northwest Europe - including Groendus , SnappCar , Next Sense , Crisp and Beyond Weather - and actively prioritise partnerships in Climate Tech where our technology delivers measurable positive impact. We build data & AI solutions. At Enjins, we operate with a product mindset, meaning we take full ownership of the technical lifecycle - from initial discovery to a scaling, production-grade engine that lives within our partners' infrastructure. At our core, we are engineers first: clean code, MLOps best practices, and system reliability. Our team is a growth-oriented group of engineers from diverse cultural, academic, and professional backgrounds. What? [You'll be doing] 👀 You will act as a hands-on engineer embedded within client teams, designing and deploying end-to-end AI/ML systems from proof-of-concept to production. Technical mastery meets high-impact client engagement. Key Responsibilities Own a feature or deployment pipeline on client projects, demonstrating technical mastery and end-to-end responsibility. Spearhead the adoption of MLOps/LLMOps best practices - feature stores, model monitoring, pipeline orchestration — to ensure client systems are scalable and reliable. Collaborate with Data Scientists and Software Engineers to design and implement robust data pipelines and model APIs. Bridge the gap between data science and business value by translating technical findings into clear, actionable insights for non-technical stakeholders What success looks like (within 6 Months) 🎯 A concrete example of what this could mean in practice: within your first months, you might build a predictive energy-demand model for a Climate Tech client - going from raw sensor data all the way to a monitored, production API. That's the kind of real-world impact we're after. Within 1 Month Complete the Enjins AI Leap onboarding programme, understanding our approach and becoming a certified cloud practitioner (AWS, Azure, or GCP). Start your first client project — always alongside an experienced Enjins engineer who acts as your technical buddy and mentor. Get introduced to your dedicated Lead and Buddy, who will support your first two months of onboarding. Within 3 Months Develop and implement robust AI/ML applications for your client, building new solutions and resolving integration challenges — laying the foundation of your AI engineering skills. Receive multiple feedback moments with your project team before and after client meetings to sharpen your consulting and project management skills. Within 6 Months Identify new tools, methods, and processes that work best — and share them with the team. Help in the interview process for additional AI Engineers joining Enjins' growing team. Have meaningfully accelerated your client's velocity.