Job Description

We're partnering with a major technology organisation to find the senior leader who will build the data foundation behind its next generation of AI.

This role is about building the enterprise data infrastructure that allows AI, GenAI and Agentic AI to work — reliably, securely and at scale.

The Role:

You will own the strategy, architecture and engineering of reusable AI-ready data products, semantic knowledge assets, context engineering and retrieval capabilities across a large and complex enterprise.

Your work will sit at the intersection of:

AI-ready data architecture

Knowledge graphs & semantic layers

Vector search & retrieval

RAG & Agentic AI

Context engineering & agent memory

Data products & enterprise data platforms

AI data governance & trust

The ambition

Build once. Scale everywhere.

Create reusable data and knowledge foundations that can power AI applications, intelligent agents, analytics and automation across multiple business domains.

What you'll actually do

Architect the AI-ready data foundation

Define the enterprise AI-ready data strategy
Establish reusable data products, semantic foundations and retrieval services
Drive architecture across data platforms, knowledge assets, context services and AI data infrastructure

Build the organisation

Lead multidisciplinary teams across data engineering, data products, knowledge engineering, semantic technologies, AI governance and platform engineering
Build capability in knowledge graphs, semantic modelling, context engineering and AI-ready data operations

Make enterprise data understandable to AI

Build semantic models, knowledge graphs, taxonomies and business context
Create trusted, discoverable and governed data products that improve AI reasoning and decision-making

Build the context layer for AI and agents

Architect enterprise retrieval and context engineering capabilities
Establish standards for RAG, embeddings, vector search, context orchestration and evaluation
Develop reusable patterns for agent memory and contextual reasoning

Keep it production-grade

Challenge data architectures, pipelines, semantic models and retrieval frameworks
Drive improvements in data quality, freshness, reliability, scalability, latency and cost
Lead optimisation of the data foundations supporting production AI

Make AI trustworthy

Define standards for data quality, lineage, metadata, privacy, security and access
Build governance that enables trusted AI deployment without slowing innovation
Ensure AI data assets meet regulatory and security requirements

What we are looking for:

Senior Data Engineering Leader who has moved into AI

AI Infrastructure / Platform Leader building the foundations for GenAI

Data & AI Product Leader who understands how data becomes an AI capability

Knowledge Engineering / Semantic Technology Leader working at enterprise scale

Enterprise Architect who has gone deep into modern AI data architectures

What matters most is that you have built and scaled complex data and AI foundations, not simply advised organisations on them.

You'll need deep experience across modern data engineering combined with technologies such as:

Knowledge graphs
Semantic modelling
Vector databases / vector retrieval
RAG
Context engineering
AI-ready data architectures
Data products
Enterprise data platforms
AI data governance

And critically, you'll need the leadership capability to turn these technologies into enterprise-scale business outcomes.

Equal Opportunity Statement

TENTEN Partners is an equal opportunity firm and is committed to providing equal employment opportunities to all qualified individuals without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or any other protected characteristic as outlined by applicable laws.