AI Solution Architecture

Zohorecruit; City of Edinburgh; Hybrid; GBP 90,000 - 130,000; Full time

Job summary

Zohorecruit in the United Kingdom is seeking a Data/AI Solutions Architect to design scalable, secure data and AI ecosystems. You will drive strategy for ML, LLMOps, RAG, and GCP migrations, bridging business needs with technical execution, and ensure governance, security, and ethical AI standards.

Key duties include defining end-to-end architectures on GCP, leading technical decisions, integrating API/microservice patterns with Istio and Apigee, and collaborating with engineering, data science,

Qualifications

• Experience designing AI/ML data architectures for cloud platforms.
• Ability to lead architecture decisions and communicate trade-offs to stakeholders.
• Knowledge of data governance, security, and risk management in cloud environments.
• Experience with agentic AI, LLM-based systems, and RAG patterns.
• Familiarity with multi-cloud or hybrid cloud environments.
• Strong collaboration with engineering, data science and business teams.

Responsibilities

• Strategy & Design: Define end-to-end architectures for AI, ML, data, and agentic AI solutions on Google Cloud Platform.
• Technical Leadership: Deliver secure solutions using GCP services and event-driven patterns.
• Cloud, Platform & Integration: Apply understanding of Kubernetes, service mesh, ingress, workload identity and security boundaries.
• Design Patterns: Implement API and service integration patterns with Istio, Apigee, and modern microservices.
• Governance & Compliance: Ensure solutions meet regulatory and security standards.
• Collaboration: Work with engineering, data science, and business teams to translate requirements into designs.

Skills

Cloud architecture

GCP/Azure

Data & AI knowledge

Stakeholder leadership

Communication

Security & governance

LLMOps/RAG

Tools

BigQuery

Vertex AI

GKE

Looker

Dataflow

Pub/Sub

Cloud Run

Apigee

Istio

Kubernetes

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 asBigQuery, 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 enterpriseAuthN/AuthZpatterns (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 foragentic 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 ofLangChain/LangGraph, RAG patterns, and AI workflow orchestration.
• Experience in multi cloud (GCP/Azure/AWS) or hybrid environments.
• Understanding of enterprise integration and event architecture.