Principal AI/ML Architect (m/f/d) at Wavestone Management Advisory UK Ltd, London, 16 Months, £Contract Rate

Principal AI/ML Architect (m/f/d)

We are seeking a Principal AI Architect to provide advanced technical leadership and strategic direction in the design and implementation of enterprise-class platforms for AI/ML. This role acts as a bridge between business strategy and technical execution and enables the development of AI capabilities through cloud-native infrastructure design, workflow automation, and the operationalization of AI/ML models using modern MLOps practices. The successful candidate will work closely with executives and cross-functional technical teams to deliver scalable, compliant, and high-performing AI solutions.

Your tasks

• Drive the organization's AI/ML architecture strategy, frameworks, and best practices
• Develop roadmaps for AI initiatives aligned with business objectives and future technology direction
• Evaluate emerging AI/ML technologies, platforms, and cloud services to recommend adoption where appropriate
• Architect scalable, secure, and reliable AI/ML systems from data ingestion and feature engineering to model monitoring
• Design and operationalize cloud-native AI capabilities using modern DevOps and MLOps practices
• Oversee the design and provisioning of infrastructure to support AI/ML workloads and monitor platform performance
• Establish governance frameworks for model management, monitoring, retraining, and risk mitigation
• Provide technical leadership and mentorship to AI engineers, data scientists, and development teams
• Communicate complex AI concepts and strategies in clear, business-relevant terms to stakeholders

Must have competences

• Advanced technical leadership and strategic guidance in designing and implementing enterprise-grade AI/ML platforms and solutions
• Proven ability to develop AI/ML architecture strategies, frameworks, and roadmaps aligned with business objectives
• Deep knowledge of Machine Learning, Deep Learning, Natural Language Processing, and emerging paradigms including Generative AI and Agentic AI
• Hands-on experience designing and scaling AI solutions using frameworks such as TensorFlow, PyTorch, LangChain, and Semantic Kernel
• Proven ability to architect and deploy AI/ML solutions on leading cloud platforms including AWS, Azure, and Google Cloud Platform
• Expertise in containerized environments using Docker and Kubernetes with a strong understanding of cloud-native design principles
• Advanced programming proficiency in Python with a solid foundation in software engineering principles for building production-grade systems
• Strong command of data pipeline design and big data technologies including Apache Spark, Kafka, and Airflow
• Proficiency in implementing MLOps and CI/CD pipelines for model versioning, automated deployment, monitoring, and life cycle management
• Extensive experience in designing and implementing end-to-end AI pipelines from data ingestion to production with reliability and efficiency
• Experience with Large Language Models (LLMs), Generative AI systems, vector databases, and Retrieval-Augmented Generation (RAG)
• Ability to establish governance frameworks for model management, ethical AI standards, data privacy, and regulatory compliance
• Excellent communication and stakeholder management skills with the ability to translate complex AI concepts into clear business value
• Bachelor's or Master's degree in Computer Science, Data Science, or a related technical field

Nice to have competences

• Advanced technical degree (eg, PhD) in a relevant field providing a competitive edge
• Experience with specific platforms and tools such as Databricks, AI Foundry, and Amazon Bedrock for operationalizing AI models
• Proven track record of successfully leading AI transformation projects in large-scale enterprise environments
• Experience in complex AI platform design integrating a diverse range of open-source and commercial technologies
• Familiarity with model interpretability and evaluation techniques such as SHAP or LIME

Additional information
The role operates in a flexible deployment model that includes on-site, nearshore, and offshore options, with workstreams and priorities defined jointly.