Lead AI Architect (Enterprise AI)

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 Lead AI Architect (Enterprise AI) for a 12 Month contract based in London or Edinburgh (Hybrid - 3 days per week in the office).

Join us as a Lead AI Architect (Enterprise AI).

As Lead AI Architect (Enterprise AI), you will drive the design and delivery of a next-generation enterprise AI ecosystem, embedding intelligent capabilities across the organisation. You will define the architectural vision and standards that enable scalable, secure, and business-aligned AI solutions, supporting a major transformation programme within Computershare.

Your key responsibilities will include:

• Define and own the enterprise AI architecture, including model strategy, orchestration frameworks, APIs, and integration standards.
• Establish architectural patterns for Generative AI, agentic systems, retrieval-augmented generation, and data pipelines at scale.
• Lead the selection and optimisation of the AI technology stack, balancing capability, cost, risk, and vendor considerations.
• Drive the adoption of shared, governed AI platforms and reusable components across multiple workstreams.
• Provide architectural leadership and oversight, ensuring AI solutions are scalable, secure, and aligned with enterprise standards.
• Embed Responsible AI, security, governance, and observability into all AI solutions as they move into production.

What you will bring to the role:

• Extensive experience in enterprise or solution architecture, with a strong focus on AI, machine learning, or distributed systems.
• Proven expertise in Generative AI technologies, including Large Language Models, agentic frameworks, and vector databases.
• Strong command of at least one major cloud platform (AWS or Azure) and modern software engineering practices.
• Demonstrated experience in financial services or another regulated industry (mandatory)
• Deep understanding of AI governance, security, and Responsible AI principles.
• Ability to engage and influence senior stakeholders, translating business strategy into architectural roadmaps.

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.