AI Engineer

• Design and implement LLM applications, agents, and workflow automations integrated with enterprise platforms.
• Implement RAG, tool/function calling, structured outputs, orchestration, and reusable AI components.
• Define evaluation strategies and implement AI observability to monitor quality, cost, and reliability in production.
• Drive production readiness: security, performance, resilience, cost controls, logging, and incident management.
• Ensure AI solutions comply with governance, data protection, and responsible AI principles.

• Strong Python engineering skills; experience building production-quality AI or ML-enabled applications.
• Hands-on experience with LLM frameworks (LangChain, LlamaIndex, or equivalent) and agent/RAG patterns.
• Experience with vector databases (Pinecone, Weaviate, or cloud-native), embeddings, and retrieval pipelines.
• Understanding of Transformer architectures, LLM failure modes, and engineering mitigations.
• Experience with ML frameworks (PyTorch/TensorFlow) and Microsoft Azure, including Azure AI Foundry.
• Experience with AI observability tooling (e.g. LangSmith, MLflow) and Agile delivery practices.
• Strong communication skills; comfortable working with technical and non-technical stakeholders.

Desirable: experience in financial services or other regulated environments.

Our client is a globally recognised leader in private markets investing with over 30 years of experience and approximately $80.bn AUM. Operating across private equity, infrastructure, real assets, and private credit, they serve institutional private wealth clients worldwide.