AI Engineer

• Cross-functional Collaboration: Working with software engineers, DevOps, and product teams
• Rapid Prototyping: Building and deploying MVPs
• Understanding of ML & LLM Techniques: To support integration, scaling, and responsible deployment
• Prompt Engineering: Designing and optimising prompts for LLMs across use cases

Model Evaluation & Monitoring

• Evaluation Metrics: Perplexity, relevance, response quality, user satisfaction
• Monitoring in Production: Drift detection, performance degradation, logging outputs
• Evaluation Pipelines: Automating metric tracking via MLflow or custom dashboards
• A/B Testing: Experience evaluating GenAI features in production environments

We are seeking Engineers skilled in python with a strong focus on GenAI AI and LLMs to lead the integration of cutting-edge language technologies into real-world applications.

If you're someone passionate about building scalable, responsible, and high-impact GenAI solutions then this could be for you!

We're looking for Engineers offering competent core technical skills in Python Programming, Data Handling with NumPy, Pandas, SQL, and use of Git/GitHub for version control.

Any experience with these GenAI Use Cases would be relevant and desirable; Chatbots, copilots, document summarisation, Q&A, content generation.

To help make your application as relevant as possible, please ensure your CV demonstrates any prior experience you have relating to the below;

System Integration & Deployment

• Model Deployment: Flask, FastAPI, MLflow
• Model Serving: Triton Inference Server, Hugging Face Inference Endpoints
• API Integration: OpenAI, Anthropic, Cohere, Mistral APIs
• LLM Frameworks: LangChain, LlamaIndex - for building LLM-powered applications
• Vector Databases: FAISS, Weaviate, Pinecone, Qdrant (Nice-to-Have)
• Retrieval-Augmented Generation (RAG): Experience building hybrid systems combining LLMs with enterprise data

MLOps & Infrastructure

• MLOps: Model versioning, monitoring, logging
• Bias Detection & Mitigation
• Content Filtering & Moderation
• Explainability & Transparency
• LLM Safety & Guardrails: Hallucination mitigation, prompt validation, safety layers
• Azure Cloud Experience