Artificial Intelligence Engineer

AI Solution Development • Design, develop and deploy AI-powered applications and services. • Build scalable agentic AI solutions using modern orchestration frameworks. • Develop RAG pipelines using vector embeddings, semantic search and knowledge retrieval patterns. • Implement conversational AI assistants and intelligent workflow automation. • Integrate AI models with enterprise systems, APIs and data platforms. • Develop prompt engineering, evaluation and guardrail frameworks. Machine Learning and LLM Engineering • Train, fine-tune and optimise machine learning and generative AI models where appropriate. • Build model evaluation and monitoring capabilities. • Develop model serving and inference pipelines. • Implement responsible AI controls and validation processes. • Evaluate emerging AI technologies and recommend adoption opportunities. Platform and Cloud Engineering • Build and deploy solutions on Google Cloud Platform. • Develop containerised applications using Docker and Kubernetes. • Work with GKE, Vertex AI, BigQuery, Cloud Run and related GCP services. • Implement CI/CD pipelines and automated testing frameworks. • Ensure scalability, resilience, security and observability of production services. Data and Integration • Integrate AI solutions with structured and unstructured data sources. • Build ingestion pipelines from SharePoint, APIs, databases and cloud storage. • Develop vector stores and embedding pipelines. • Work closely with Data Engineers to optimise data access patterns.