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