AI Engineer

AI Engineer – Contract Edinburgh (2 days onsite per week) Long-term Contract Competitive Day Rate GCP-Focused Environment We’re looking for an experienced AI Engineer to join a growing team delivering enterprise-scale AI and Generative AI solutions within a Google Cloud Platform (GCP) environment. This is a long-term contract opportunity for someone who enjoys building production-ready AI systems, deploying scalable ML pipelines, and working across modern LLM and cloud-native technologies. Responsibilities Design, develop, and deploy AI/ML and Generative AI applications within a GCP ecosystem Build and optimise LLM-powered applications including RAG pipelines, semantic search, AI agents, and intelligent automation workflows Develop scalable ML pipelines covering data ingestion, training, evaluation, deployment, and monitoring Work with embeddings, vector databases, prompt engineering, and model optimisation techniques Build cloud-native AI services using GCP technologies such as Vertex AI, BigQuery, Cloud Run, GKE, and Pub/Sub Collaborate with engineering, data, and business teams to deliver production-grade AI solutions Implement CI/CD, observability, security, and governance best practices for AI systems Support rapid prototyping and experimentation across new AI initiatives Required Skills & Experience Strong commercial experience as an AI Engineer, ML Engineer, Applied AI Engineer, or Data Scientist Hands-on experience with Generative AI and modern LLM ecosystems Experience building RAG systems, AI agents, or LLM-powered enterprise applications Strong Python engineering skills and experience with frameworks such as PyTorch, TensorFlow, Scikit-learn, LangChain, or similar Strong experience working within GCP environments Experience with Vertex AI, BigQuery, GKE, Cloud Run, or related GCP services Familiarity with vector databases, embeddings, and semantic retrieval systems Experience with Docker, Kubernetes, APIs, backend systems, and CI/CD pipelines Strong understanding of scalable production AI deployment Desirable Experience Experience with Gemini, OpenAI, Claude, Bedrock, or other enterprise LLM platforms Exposure to MLOps tooling such as MLflow, Airflow, Kubeflow, or Databricks Experience with streaming/data processing tools such as Spark or Kafka Previous experience within enterprise or highly regulated environments