Artificial Intelligence Engineer

Nature of tasksDevelop, integrate, and maintain AI and machine learning models within business applications.Build and optimise data pipelines for model training, evaluation, and deployment.Implement Large Language Model (LLM) based solutions (e.g., RAG, prompt engineering, finetuning).Collaborate with product owners and domain experts to translate business needs into AI solutions.Deploy models using Machine Learning Operations (CI/CD, monitoring, versioning).Evaluate model performance, fairness, and reliability.Integrate cloud-based AI services (Azure, AWS, GCP) into enterprise systems.Ensure compliance with data governance, security, and ethical AI guidelines.Document AI workflows, architectures, and operational procedures.Support cross functional teams in adopting AI capabilities.General competencies and skills minimumExperience in relevant programming skills (e.g. Python, SQL, Java)Experience of machine learning fundamentals and model lifecycleExperience to build and maintain data pipelinesKnowledge of APIs, microservices, and containerization (Docker, Kubernetes)General competencies and skills advantageousExperience with AI/ ML frameworks (e.g. TensorFlow, PyTorch)Experience with LLMs and generative AI conceptsExperience with cloud platforms (e.g. Azure AI, Open Source AI)Education and professional experienceUniversity degree with minimum 6 years of experience in IT OR non university degree with minimum 12 years of experience in ITMinimum 4 years of experience in designing and implementing AI solutions including the application of LLMsCertification and StandardsMandatory certification, issued by a third party over which the tenderer cannot exercise a decisive influence (one of):Azure AI EngineerAWS Certified Machine LearningGoogle Professional Machine Learning Engineeror equivalent to the above