AI Platform Manager

The organisation is seeking an AI Platform Manager to lead the strategy, direction, and operational excellence of its AI platform. This role oversees three engineering teams responsible for building and scaling the platform capabilities that power AI and LLM initiatives across the business.

You will shape the platform roadmap, drive alignment with senior stakeholders, and ensure the platform provides the tooling, infrastructure, and governance needed for teams to build AI solutions at scale.

Key Responsibilities

Lead and coordinate three engineering teams focused on AI platform development, infrastructure, and tooling.

Define and evolve the AI platform strategy, covering LLM integration, model lifecycle, evaluation, governance, and developer enablement.

Partner with product, engineering, and data stakeholders to align priorities and ensure platform capabilities meet organisational needs.

Provide direction on best practices for LLM usage, retrieval workflows, evaluation frameworks, and responsible AI.

Oversee architectural decisions, tooling selection, and AWS-based infrastructure supporting AI workloads.

Ensure the platform is scalable, secure, cost-efficient, and compliant with organisational and regulatory standards.

Drive adoption of platform capabilities through communication, enablement, and cross-team collaboration.

Monitor platform performance, operational health, and usage patterns to guide continuous improvement.

Leadership Experience managing multiple engineering or platform teams.

Strong expertise in LLMs, generative AI, embeddings, vector search, and evaluation tooling.

Deep understanding of AWS services and cloud-native architectures.

Proven ability to influence senior stakeholders and drive cross-functional alignment.

Experience defining platform roadmaps and delivering large-scale technical initiatives.

Solid grounding in AI governance, responsible AI, and data security.

Preferred Qualifications

Background in AI platform engineering, ML platform management, or internal developer platforms.

Familiarity with RAG pipelines, agentic workflows, and model fine-tuning.

Experience optimising AI workloads for cost and performance.

Ability to translate complex technical concepts into clear business narratives.

What Success Looks Like

Three teams operating with strong alignment, autonomy, and delivery momentum.

A clear, widely adopted AI platform strategy.

Strong trust and alignment with senior stakeholders.

Scalable, secure, and cost-efficient AI capabilities powering multiple products.

A well-governed environment for experimentation and productionisation of LLM-based features.