Lead AI Architect

Job Description

. As a Lead AI Architect (Principal IT Architect), you will be responsible for building, deploying, and optimizing enterprise-grade AI/ML and Generative AI solutions.

. This role leads the design and implementation of scalable AI architectures, LLM pipelines, and data platforms, while working closely with architects, engineering, and product teams to deliver production-ready, secure, and high-performing AI systems.

. What will you do Enterprise AI Architecture & Strategy Design, define, and maintain the organisation's enterprise.

. AI architecture and standards Ensure AI solutions align with overall IT architecture, security, and governance principles.

. Lead the team to ensure designs and code conform to approved architecture and standards AI/ML & GenAI Solution.

. Delivery Build, deploy, and optimise AI/ML and GenAI applications Implement LLM pipelines, RAG workflows, retrieval strategies, and vector database integrations.

. Fine-tune, evaluate, and optimise LLMs for latency, accuracy, cost, and safety Data & Model Engineering Build data ingestion, feature engineering, and model training pipelines Implement embeddings, retrieval optimisation, and model evaluation techniques.

. Ensure AI solutions meet data quality, performance, and scalability requirements Platform, MLOps & Observability Develop APIs, microservices, and automation supporting AI capabilities Implement monitoring, logging, prompt evaluation, and automated testing for AI systems.

. Apply MLOps / GenAIOps practices for model lifecycle management.

. Collaboration & Quality Assurance Collaborate with architects, engineers, and product teams to deliver production-ready.

. AI solutions Participate in peer reviews to improve solution quality, performance, and maintainability.

Qualifications

. 10+ years of IT development experience, including 5+ years implementing AI solutions.

. Strong Python programming skills with AI/ML frameworks (PyTorch, TensorFlow)

. Hands-on experience with LLM frameworks and libraries (Transformers, LangChain, LlamaIndex)

. Experience implementing RAG workflows, embeddings, and vector databases (Pinecone, Milvus, Weaviate)

. Experience with cloud AI services, containerisation (Docker), Kubernetes, and serverless architectures.

. Familiarity with MLOps / GenAIOps tools (MLflow, Vertex AI, SageMaker, Databricks)

. Strong grounding in data engineering, API development, and observability.

. Understanding of responsible AI, prompt engineering, evaluation, and data governance frameworks.

. Proven experience contributing to or leading large-scale AI or data initiatives.

. Bachelor's degree in Computer Science, Information Systems, or a related field Master's degree in a related field (preferred).