Architecture Lead

Lead AI Platform Architect

The Lead AI Platform Architect defines the architecture, technology strategy and roadmap for our client’s enterprise AI platform, enabling secure, scalable and reusable AI capabilities across the organisation. Working at the centre of the AI platform ecosystem, the role supports consistent AI solution delivery while ensuring alignment with business priorities, technology advancements and enterprise governance requirements.

Role Overview

The role provides technical authority across AI platform strategy, foundation models, agentic AI, model lifecycle management, AI engineering frameworks and platform capabilities. It works closely with Enterprise Architecture, AI Platform Engineering, AI Platform Operations, Cybersecurity, AI Solution Architects and business stakeholders. Success means continuously evolving an interoperable, reliable and enterprise-ready AI platform while providing technical direction to architects and engineers.

Key Skills & Experience

Strong foundation in enterprise platform architecture, distributed systems and cloud-native technologies

At least 10 years of experience in enterprise architecture, platform architecture, software architecture or cloud architecture, designing large-scale enterprise platforms

At least 3 years of experience designing AI, Machine Learning or Generative AI platforms in an enterprise environment

Proven experience defining platform architecture, technology roadmaps, architecture standards and reusable platform capabilities

Experience leading architecture governance, including presenting architecture proposals to senior management and Architecture Review Boards

Experience working across Enterprise Architecture, Engineering, Infrastructure, Cybersecurity, Data and Business teams

Strong knowledge of enterprise AI platform architecture, including AI application platforms, AI engineering ecosystems, Model-as-a-Service and agentic AI platforms

Strong understanding of foundation models, Large Language Models, Small Language Models, multimodal AI and enterprise AI deployment strategies

Experience defining AI model lifecycle architecture, including model evaluation, fine-tuning strategies, deployment, versioning, monitoring and governance

Strong understanding of cloud-native, hybrid cloud and on-premises platform architectures, distributed computing and container orchestration principles

Good understanding of enterprise AI application patterns, including Retrieval-Augmented Generation, AI agents, workflow orchestration, Model Context Protocol, API integration and enterprise integration architectures

Strong knowledge of enterprise architecture principles, distributed systems, microservices, event-driven architectures and API-first design

Experience defining architecture standards for AI security, Responsible AI, data governance, model governance, privacy and regulatory compliance

Good understanding of AI platform reliability, scalability, observability, resiliency and performance optimisation principles

Strong ability to evaluate emerging AI technologies and translate technology trends into enterprise platform capabilities, architecture standards and technology roadmaps

Strong strategic, analytical and systems thinking, with the ability to simplify complex architecture and technology decisions for diverse stakeholders

Excellent collaboration and stakeholder management skills across Enterprise Architecture, AI Solution Architecture, Platform Engineering, Platform Operations, Cybersecurity and Business teams

Strong communication, presentation and documentation skills, with experience presenting architecture proposals and influencing senior management and governance boards

Proven technical leadership and mentoring skills, with the ability to guide architects and engineers, influence platform direction and drive architecture best practices

Strong innovation mindset and continuous learning, with a passion for exploring emerging AI technologies and translating industry trends into enterprise platform capabilities

Key Responsibilities

Define and maintain the enterprise AI platform architecture, technology roadmap and reference architecture for the central AI platform

Establish reusable AI platform capabilities, architectural principles, design standards and technical frameworks

Evaluate, benchmark and recommend hosted, self-hosted and open-weight foundation models against business, technical and governance requirements

Engage with technology partners, cloud providers, AI vendors and the wider technology ecosystem to assess emerging platform capabilities and products

Lead proof-of-concept, technology evaluation and pilot initiatives for emerging AI technologies, frameworks, platforms and comm