AI Architect

GCS Recruitment; Greater London; Hybrid; GBP 100,000 - 140,000; Full time

Job summary

GCS Recruitment is partnering with a major UK energy-sector organisation to hire an AI Architect to shape and lead the production AI platform on Microsoft Azure. You will set standards, governance, and integration patterns for enterprise AI across the organisation and act as the technical authority guiding secure, scalable AI deployments.

The role focuses on defining path-to-production for AI agents, evaluating technologies, and advising CIO-level stakeholders on platform choices and

Qualifications

• Proven experience as AI Architect or related lead role in enterprise AI.
• Strong hands-on architecture experience within Microsoft Azure.
• Delivery of production-grade Generative AI solutions.

Responsibilities

• Own and evolve the architecture for a production-grade Azure AI platform.
• Define standards and governance for enterprise AI, GenAI, RAG, and Agentic AI solutions.
• Design and implement enterprise integration patterns across core business systems.
• Lead architecture decisions around Azure AI services and security controls.
• Establish the path-to-production framework for AI agents and cost management.
• Provide technical leadership across multiple workstreams and stakeholders.

Skills

AI architecture

Enterprise architecture

Stakeholder communication

Security & compliance

Governance & standards

Tools

Azure OpenAI

Azure AI Foundry

Azure AI Search

Azure API Management

Entra ID

Azure Landing Zones

Job description

AI Architect - Enterprise GenAI Platform (Azure)

UK-Based | Hybrid Working
Contract Opportunity | Immediate Start Preferred

The Opportunity

We are partnering with a major UK energy-sector organisation undertaking a large-scale Enterprise AI transformation programme and are looking for an experienced AI Architect to shape and lead the architecture of their production AI platform.

This is a high-impact role where you will act as the technical authority for a rapidly evolving AI ecosystem, defining enterprise standards, governance, integration patterns, and the path to production for AI and agentic solutions across the organisation.

You'll work closely with senior stakeholders, architects, security teams, product owners, and engineering teams to establish a scalable, secure, and governed AI platform that supports enterprise-wide adoption.

What You'll Be Doing

• Own and evolve the architecture for a production-grade Azure AI platform.
• Define standards and governance for enterprise AI, GenAI, RAG, and Agentic AI solutions.
• Design and implement enterprise integration patterns across HR, Service Management, and other core business systems.
• Lead architecture decisions around Azure OpenAI, Azure AI Foundry, Azure AI Search, APIM, Entra ID, and AI orchestration services.
• Establish the path-to-production framework for AI agents, including evaluation, security, observability, deployment, and cost management.
• Create reusable reference architectures, patterns, and guardrails for wider teams.
• Review AI solution designs and provide technical leadership across multiple workstreams.
• Advise senior stakeholders up to CIO level on architectural strategy, platform selection, and build-versus-buy decisions.
• Drive secure, compliant AI adoption within a regulated enterprise environment.

Essential Experience

• Proven experience as an AI Architect, Enterprise Architect, Solution Architect, or Lead AI Engineer.
• Strong hands-on architecture experience within Microsoft Azure.
• Expertise with:
  • Azure OpenAI
  • Azure AI Foundry
  • Azure AI Search
  • Azure API Management (APIM)
  • Entra ID
  • Azure Landing Zones
• Experience delivering production-grade Generative AI solutions, not just proofs of concept.
• Strong knowledge of:
  • RAG architectures
  • Agentic AI systems
  • Multi-agent orchestration
  • Model Context Protocol (MCP)
  • LLM governance and evaluation frameworks
• Enterprise integration experience covering:
  • APIs
  • Event-driven architecture
  • Identity propagation
  • SaaS platform integrations
• Strong understanding of security, compliance, data classification, auditing, and data residency requirements.
• Ability to communicate architecture decisions clearly to both technical and executive stakeholders.

Desirable Experience

• Energy, utilities, public sector, or other highly regulated environments.
• Workday and/or ServiceNow integrations.
• Semantic Kernel, LangGraph, or Foundry Agent Service.
• Azure Monitor, Application Insights, Langfuse, or Arize.
• Secure AI deployment patterns including private networking and customer-managed encryption.
• Azure Solutions Architect Expert and/or Azure AI Engineer certifications.
• Consultancy or client-facing delivery experience.