About the client
Our client is an AI transformation studio that partners with large, ambitious organizations to design and build applied AI products with measurable business impact. They help enterprise and scale-up clients move beyond experimentation by embedding AI directly into operations, decision-making, and products. Their work spans industries, with a strong focus on production-ready AI, solid engineering, and real-world adoption.
About the role
Our client is looking for an AI engineer to design and build AI systems that power real, production-grade applications. This role is focused on applied AI engineering rather than research in isolation. You will work hands-on with machine learning models and large language models, building agentic workflows, orchestration layers, and AI-driven services that integrate directly into business-critical systems.
You will be responsible for taking AI capabilities from idea to deployment, ensuring they are reliable, scalable, and maintainable in real client environments.
What you’ll do
You will design, implement, and deploy AI systems that support automation, decision-making, and new workflows for enterprise clients. This includes building and integrating machine learning and LLM-based solutions, developing agentic workflows, and orchestrating multi-step AI processes.
You will work primarily in Python, using modern machine learning and LLM tooling, and package models into APIs and services that integrate with back-office systems and customer-facing applications. You will collaborate closely with engineers across disciplines to connect models to structured and unstructured data sources, data pipelines, and production software systems.
Beyond model development, you will take ownership of evaluation, monitoring, performance optimization, and MLOps practices to ensure AI solutions remain robust and scalable over time.
What you bring
You have strong experience building AI-powered systems in production environments and are comfortable working across the full AI lifecycle, from data and modeling to deployment and monitoring. You are proficient in Python and experienced with machine learning frameworks and modern LLM ecosystems.
You understand how to work with structured and unstructured data, how to evaluate model performance in real-world settings, and how to design systems that balance accuracy, latency, cost, and reliability. You are comfortable wrapping AI logic into services that other engineers can safely and easily consume.
How you work
You approach AI as an engineering discipline, with a strong focus on maintainability, observability, and real-world constraints. You enjoy working in multidisciplinary teams and are comfortable operating in a consulting-style environment, where each project brings new domains, data, and challenges.
You care about building AI systems that are actually used, trusted, and deliver long-term value.
Growth and impact
From early on, you’ll help shape how AI systems are designed, built, and deployed across projects. Over time, you’ll take ownership of increasingly complex AI architectures, contribute to internal tooling and best practices, and help raise the bar for applied AI engineering across the team.
Contract and setup
This role is open to both permanent employment and long-term contract arrangements. Depending on preference and location, our client can offer either a standard employment contract or a contractor-based setup.