Data & Knowledge Architect (AI data foundations)

Computershare is global leader in financial administration with over 12,000 employees across more than 22 different countries. Many of the world's leading organisations use us to streamline and maximise the value of relationships with their investors, employees, creditors and customers.

Our global footprint means we have the scale to maintain robust compliance, audit, risk, financial crime, disaster recovery and business continuity planning programs - offering peace of mind to our clients and their customers.

AMS is a global workforce solutions partner committed to creating inclusive, dynamic, and future-ready workplaces. We help organisations adapt, grow, and thrive in an ever-evolving world by building, shaping, and optimising diverse talent strategies.

We partner with Computershare to support their contingent recruitment processes. Acting as an extension of their recruitment teams, we connect them with skilled interim and temporary professionals, fostering workplaces where everyone can contribute and succeed.

On behalf of Computershare, we are looking for a Data & Knowledge Architect(AI data foundations) for a 12 Months contract based in London or Edinburgh (Hybrid - 3 days per week in the office).

Join us as a Data & Knowledge Architect(AI data foundations).

As a Data & Knowledge Architect, you will define how enterprise data is structured, governed, and transformed into AI-ready assets that power intelligent systems at scale. You will design the knowledge foundations that enable accurate, contextual, and trusted AI across agentic platforms, conversational systems, and advanced analytics.

Your key responsibilities will include

Define and contribute to the enterprise data and knowledge architecture, supporting AI platforms and use cases across the organisation.

Design and implement knowledge foundations, including taxonomies, ontologies, metadata, and knowledge graphs to support AI retrieval and reasoning.

Establish scalable patterns for data ingestion, transformation, and retrieval across structured and unstructured data sources.

Support the development of retrieval-augmented generation (RAG) frameworks, including embedding strategies, vector search, and data pipelines.

Embed data governance, security, privacy, and Responsible AI practices across the knowledge layer.

Collaborate with architecture, engineering, and business teams to ensure data readiness, quality, and accessibility for AI use cases .

What you will bring to the role

Strong experience in data architecture, data engineering, or knowledge architecture within enterprise environments.

Hands-on experience with AI data foundations, including embeddings, vector databases, and retrieval mechanisms (RAG).

Proven track record working on large-scale transformation programmes, ideally within financial services (preferred/strong advantage).

Solid understanding of data governance, quality, lineage, and security in regulated environments.

Experience with modern cloud data platforms (AWS, Azure, or similar) and associated tooling.

Strong stakeholder collaboration skills, with the ability to translate business needs into scalable data solutions.

Next steps

Computershare are dedicated to providing you with the opportunity to succeed on your own merits, starting from the application process. Our goal is to create an environment where everyone feels valued, to remove barriers and obstacles and ensure equal opportunities for all.

If you are interested in applying for this position and meet the criteria outlined above, please click the link to apply and speak to one of our Sourcing Specialists.

AMS are committed to providing all our candidates with the opportunity to perform at their best throughout the recruitment process. Please let us know if you require any additional support or reasonable adjustments during the screening process and we will work with you and Computershare to identify the best solution to meet your requirements.

We can only accept workers operating via an Umbrella or PAYE engagement model.

Please note that for the duration of this assignment you will be working as an external resource engaged by AMS.