AI Architect - #2177263

AI Solutions Architect

Job Title: AI Solutions Architect

Location: Edinburgh (Hybrid – 2 days onsite per week)

Contract Length: 6 months

Day Rate: £400–£450 per day

Contract Type: Contract

Role Overview

We are seeking an experienced AI Solutions Architect to design and deliver scalable, secure, and resilient data and AI solutions within a cloud-based enterprise environment. The successful candidate will play a key role in shaping AI and data architecture, supporting strategic initiatives across Machine Learning, Generative AI, LLMOps, Retrieval-Augmented Generation (RAG), agentic AI, and cloud migration.

Working closely with engineering, data science, security, and business stakeholders, you will translate complex business requirements into robust technical architectures. You will ensure solutions align with enterprise technology standards, regulatory requirements, and best practices across cloud security, data governance, and responsible AI.

Key Responsibilities

Architecture & Technical Strategy

• Define end-to-end architectures for data, AI, Machine Learning, and agentic AI solutions running on Google Cloud Platform (GCP).
• Develop scalable, secure, and resilient cloud-native architectures aligned with enterprise technology strategy and engineering standards.
• Lead architectural design decisions, evaluate technology options, and communicate technical trade-offs.
• Contribute to architectural governance forums, including Architecture Review Committees (ARC) and Architecture Working Groups (AWG).

Cloud & Data Engineering

• Architect solutions using GCP services, including BigQuery, Cloud Run, GKE, Cloud Storage, Dataflow, Pub/Sub, Vertex AI, Looker, and Cloud Composer.
• Support cloud migration and modernisation initiatives, including large-scale data migrations, ETL transformation, and legacy platform decommissioning.
• Apply modern data movement, integration, and event-driven architecture patterns.
• Leverage experience across GCP, Azure, AWS, or hybrid cloud environments where appropriate.

AI, Machine Learning & Generative AI

• Design architectures for Machine Learning, LLM-based applications, RAG solutions, and agentic AI systems.
• Develop architectural patterns for AI workflow orchestration, model integration, and LLMOps.
• Evaluate and apply AI frameworks and tooling, including Vertex AI, LangChain, and LangGraph.
• Ensure AI solutions are scalable, observable, maintainable, and aligned with responsible AI principles.

Integration, Security & Platform Architecture

• Design API and microservice integration patterns using technologies such as Apigee and Istio.
• Apply Kubernetes architecture principles, including service mesh, ingress, workload identity, and network security boundaries.
• Implement enterprise authentication and authorisation patterns using OIDC, IAM roles, workload identities, and API security policies.
• Ensure appropriate controls for data protection, access management, resilience, and secure service-to-service communication.

Governance & Stakeholder Management

• Ensure architectures meet regulatory, risk management, information security, and data governance requirements.
• Collaborate with engineering teams, data scientists, platform specialists, and business stakeholders to translate requirements into actionable technical designs.
• Present architectural recommendations clearly to technical and non-technical audiences.
• Maintain alignment with enterprise architecture standards and support the delivery of high-quality technical solutions.

Essential Skills & Experience

• Proven experience as a Solutions Architect, Data Architect, AI Architect, or in a similar senior architecture role.
• Strong hands-on architectural experience with Google Cloud Platform (GCP) and cloud-native services.
• Deep understanding of modern data architecture, Machine Learning, and AI solution design.
• Experience designing architectures for Generative AI, LLM-based applications, RAG, and/or agentic AI.
• Strong understanding of cloud security, identity and access management, Kubernetes, microservices, and API integration.
• Experience with event-driven architectures and enterprise integration patterns.
• Ability to lead technical design discussions, articulate architectural trade-offs, and influence technical direction.
• Excellent stakeholder management and communication skills, including experience presenting in architecture governance forums.
• Understanding of data governance, regulatory compliance, and secure enterprise architecture principles.

Desirable Experience

• Experience in banking, financial services, or another highly regulated industry.
• Experience with Vertex AI or other AI model lifecycle and deployment tooling.
• Knowledge of LangChain, LangGraph, LLMOps, RAG frameworks, and AI workflow orchestration.
• Experience with Azure, AWS, multi-cloud, or hybrid cloud environments.
• Experience with large-scale data migration programmes and ETL modernisation.
• Familiarity with IBM DataStage decommissioning or migration to modern cloud-based data platforms.
• Experience with Apigee, Istio, and enterprise API management.

Contract Details

• Location: Edinburgh
• Working Arrangement: Hybrid, with 2 days onsite per week
• Contract Duration: 6 months
• Day Rate: £400–£450 per day
• Role Focus: AI solution architecture, GCP, data modernisation, Generative AI, and cloud integration

Ideal Candidate

The ideal candidate will combine strong cloud and data architecture expertise with a solid understanding of modern AI technologies. They will be comfortable operating at both strategic and technical levels, leading architecture decisions, engaging senior stakeholders, and designing secure, enterprise-ready solutions that support the organisation's AI and cloud transformation objectives.