AI Engineer, Agentic AI

- Design, build, and optimise agentic AI systems using frameworks such as LangChain, LangGraph, Vertex AI Agent Builder, and custom orchestration. - Build LLM-powered applications using models including GPT-4o/5, Llama3, Claude, and enterprise-grade LLM deployments. - Implement RAG and CAG architectures using Pinecone, OpenSearch, and custom vector stores. - Engineer domain-tuned embeddings using ADA-002, Gecko, Word2Vec, and BERT. - Develop scalable AI/ML microservices using Docker, Kubernetes, and CI/CD-driven automation. - Build and enhance pipelines for model evaluation, bias/drift detection, and real-time inference. - Optimise inference latency for high-volume, near-real-time applications. - Apply text clustering, N-gram analytics, sentiment modelling, and intent classification for insight extraction. - Refine conversational intent taxonomies and behavioural models for AI assistant interactions. - Use cloud services for training, deployment, and monitoring, managing datasets securely and compliantly. - Establish guardrails, safety layers, and automated evaluation frameworks to meet compliance requirements.