AI Solution Architect

Insight International (UK) Ltd; City of Edinburgh; On-site; GBP 90,000 - 140,000; Full time

Job summary

Insight International (UK) Ltd in Edinburgh seeks a Data/AI Solutions Architect to design scalable, secure data and AI systems on Google Cloud Platform, driving ML, LLMOps, RAG, and cloud migration strategies. You will bridge business needs with technical execution, engaging stakeholders and shaping architectural direction.

Lead end-to-end architectures, define patterns for API and service integration, ensure governance, risk management, and compliance, and collaborate with engineering, data

Qualifications

• Experience designing AI/ML data architectures.
• Experience with data governance and security.
• Experience migrating workloads to GCP or multi-cloud environments.
• Experience with enterprise integration and event-driven patterns.

Responsibilities

• Define end-to-end architectures for AI, ML, data, and agentic AI solutions on Google Cloud Platform.
• Deliver secure, scalable solutions using GCP services and event-driven patterns.
• Architect Kubernetes-based workloads and manage workload security boundaries.
• Design API and service integration patterns using Istio and Apigee.
• Ensure governance, risk management, and regulatory compliance.
• Collaborate with engineering, data science, and business teams to translate requirements into designs.

Skills

GCP/Azure cloud

Data & AI knowledge

Architect leadership

Communication skills

Tools

Vertex AI

LangChain

LangGraph

Kubernetes

Apigee

DataFlow

Looker

BigQuery

Cloud Run

GKE

Job description

As a Data/AI Solutions Architect, you will be responsible for designing scalable, highly secure, and resilient data and AI systems, while driving strategic initiatives including Machine Learning, LLMOps, RAG, and GCP cloud migration. This role bridges business needs with technical execution, involving stakeholder management, cloud-native architecture development, and ensuring compliance with data governance, security, and ethical AI standards.

Key Responsibilities:

• Strategy & Design: Define end to end architectures for AI, ML, data, and agentic AI solutions running on Google Cloud Platform. Develop and maintain iterative designs aligned to modern engineering practice. Ensure alignment to platform strategy, technology standards, and security controls.
• Technical Leadership: Deliver high-quality, secure solutions using GCP cloud-native services, and event-driven patterns. Architect GCP workloads using services such as BigQuery, Cloud Run, GKE, Cloud Storage, Dataflow, Pub/Sub, Vertex AI, Looker, and Cloud Composer.
• Cloud, Platform & Integration: Apply strong understanding of Kubernetes, service mesh, ingress, workload identity, and network/security boundaries.
• Design Patterns: Design and implement API and service integration patterns using Istio, Apigee, and modern microservice standards. Integrate enterprise AuthN/AuthZ patterns (OIDC, IAM roles, workload identities, Apigee security policies)
• Governance & Compliance: Ensure solutions meet strict regulatory, risk management, and security standards.
• Collaboration: Work with engineering, data science, and business teams to translate requirements into actionable, high-level designs.

Required Skills & Experience:

• Cloud Expertise: Proven experience with major Cloud platforms like GCP/Azure.
• Data & AI Knowledge: Deep understanding of modern data architecture, Machine Learning, and AI tools. Experience in largescale data migrations with ETL toolsets, DataStage decommissioning paths, or modern data movement patterns is beneficial.
• Architecture & Stakeholder Leadership: Design orchestrations and technical patterns for agentic AI, LLM based systems, RAG, and workflow orchestration. Ability to articulate trade-offs, lead design decisions, and shape technical direction.
• Communication: Strong ability to communicate complex technical concepts in the design forums and participate in architectural governance (ARC, AWG) and represent the lab's technical direction.

Background:

Experience in the banking or financial industry is beneficial.

Beneficial Skills:

• Experience with Vertex AI or other model lifecycle tooling.
• Knowledge of LangChain/LangGraph, RAG patterns, and AI workflow orchestration.
• Experience in multi cloud (GCP/Azure/AWS) or hybrid environments.
• Understanding of enterprise integration and event architecture.