Architect – AI Solutions

Aim of the role:

The AI Solutions Architect will shape and enable practical AI adoption across Redcentric’s product and service portfolio, creating customer facing offerings and internal capabilities that improve service quality, automation, productivity and operational efficiency.

The role combines AI, data, automation, security, governance and modern delivery expertise with strong architectural leadership. It will translate AI opportunities into secure, governed, repeatable and commercially viable capabilities that can be delivered and operated at scale.

A key focus is embedding AI into existing products, services, operational capabilities and delivery practices, while also developing specific AI product offerings, internal tooling, process automation, knowledge enablement and engineering accelerators.

Key responsibilities:

AI Strategy, Architecture and Governance

• Shape Redcentric’s AI strategy, roadmap and capability development plan, identifying practical opportunities across customer services, internal operations, automation and knowledge management.

• Design secure, scalable and supportable AI solutions, translating business objectives into reusable architectures, delivery patterns and implementation guidance.

• Ensure AI adoption is governed, responsible and supportable, with appropriate controls for data protection, security, access, risk, auditability and operational ownership.
AI Product and Service Development

• Develop AI-enabled product and service offerings that enhance Redcentric’s existing portfolio and can be delivered repeatedly and commercially.

• Define offering scope, service components, delivery stages, support model, commercial assumptions, customer value proposition and route from pilot to production.

• Create reusable assets such as service definitions, reference architectures, implementation guides, risk controls and customer-facing technical content.
Internal Enablement and Delivery Excellence

• Identify and deliver opportunities for AI-enabled productivity, process automation, operational improvement and knowledge enablement.

• Support internal tooling, assistants, agents and workflows that reduce manual effort, improve quality and increase operational consistency.

• Promote repeatable, controlled and secure delivery practices across AI initiatives, including testing, validation, documentation and service transition.
Customer, Commercial and External Engagement

• Act as a trusted advisor to customers, supporting discovery, use-case prioritisation, solution design and controlled adoption of AI capabilities.

• Provide technical leadership for AI-related bids, proposals, workshops, commercial opportunities and customer engagements.

• Maintain awareness of emerging AI capabilities, operating models, governance approaches and market trends to inform Redcentric’s propositions and delivery approach.

This list of responsibilities is not exhaustive, and the role holder is expected to reasonably take on any other responsibilities required to support business activities within the Redcentric Group.

Success Measures
A successful AI Solutions Architect will:

• Deliver repeatable AI architectures, delivery patterns and implementation frameworks.

• Define and mature specific AI product offerings with clear service, commercial and operational models.

• Embed AI into existing Redcentric services and internal operating capabilities.

• Improve automation, documentation, knowledge management, engineering productivity and operational efficiency.

• Support secure, governed and supportable AI adoption through modern delivery and assurance practices.

• Contribute to pipeline growth, customer satisfaction, service innovation and technical differentiation.

Person specification

The ideal candidate will be able to demonstrate the following skills and experience:

Professional Attributes
A successful AI Solutions Architect will:

• Turn emerging AI concepts into practical, supportable and repeatable capabilities.

• Take a portfolio-minded approach to enhancing existing services rather than treating AI as a standalone technology.

• Collaborate effectively across Product, Architecture, Engineering, Security, Assurance, Service…