AI Engineer

• Design, build, and deploy Generative AI models for enterprise manufacturing and operational intelligence use cases.
• Develop and maintain end to end machine learning pipelines using modern MLOps frameworks including CI and CD, observability, automated testing, and monitoring.
• Work with large scale, multi region data sets including structured and unstructured data.
• Use tools such as Hugging Face, OpenAI, vector databases, and large language model frameworks to create advanced AI solutions.
• Optimise models through fine tuning, parameterisation, prompt engineering, and performance testing.
• Develop solutions across cloud environments including AWS, Azure, or GCP.
• Collaborate with engineering, platform, and enterprise architecture teams to embed AI into a core strategic platform.
• Maintain documentation, governance, testing standards, and responsible AI practice.

Technologies:

• AI
• Airflow
• AWS
• Azure
• Bash
• Cloud
• Docker
• GCP
• JavaScript
• Kubeflow
• Kubernetes
• Machine Learning
• Python
• SQL
• Security, We are a global manufacturing enterprise undergoing a significant digital transformation and are seeking an experienced and ambitious AI Engineer specializing in Generative AI. In this role, you will directly contribute to our enterprise architecture platform used across global operations. You will have the opportunity to shape AI capability within our organization and collaborate with platform engineers, architects, and data teams building a flagship enterprise platform. We offer access to cutting-edge AI tooling, cloud infrastructure, and research, along with clear progression into senior or architecture level AI positions.

• A minimum of 3 years experience delivering live, production grade AI or machine learning systems.
• A minimum of 5 years theoretical understanding of machine learning, deep learning, NLP, and large language models.
• Strong experience with transformer models, embeddings, vector search, and Generative AI architectures.
• Practical experience using Hugging Face, OpenAI, LangChain, Retrieval Augmented Generation, and diffusion models.
• Strong MLOps experience including MLflow, Kubeflow, Airflow, Docker, Kubernetes, and CI and CD tooling.
• Strong programming skills in Python. Bash, SQL, and JavaScript are desirable.
• Proven experience working with large, complex, multi source data sets.
• Experience with consumer behavioural or market data is desirable.
• Comfortable working within agile engineering teams and enterprise environments.
• Experience with vector databases such as FAISS, Pinecone, or Weaviate is desirable.
• Knowledge of enterprise scale Retrieval Augmented Generation systems is desirable.
• Experience within global manufacturing, engineering, or industrial environments is desirable.
• Understanding of data governance, security, and responsible AI principles is desirable.