Senior Enterprise Architect (AI Focused)

Position Overview

We are seeking a Senior Enterprise Architect (AI-Focused) to lead our enterprise AI strategy and drive the design of scalable, cloud-native AI solutions. This role will focus on agentic AI, multi-agent systems, RAG architectures, and enterprise AI integration aligned to business goals.

We will establish best practices for AI architecture, orchestration, governance, and responsible AI, while partnering with cross-functional teams to deliver secure, production-grade solutions across the organisation.

We understand the need to provide a flexible working environment partnered with team collaboration and socialisation. Therefore, we operate a hybrid working model with 3 days of working from home per week. This role is based in the London office.

Key Responsibilities

• Define and lead the enterprise AI architecture strategy, aligning agentic AI capabilities with business goals
• Design and govern scalable AI architectures, including multi agent systems, data pipelines, and model lifecycle management
• Drive adoption of agentic AI frameworks and establish best practices for orchestration, tool usage, and system integration
• Architect and oversee RAG based solutions, ensuring effective retrieval pipelines, embedding strategies, and knowledge integration
• Lead integration of AI solutions across enterprise platforms, APIs, and third-party services
• Establish standards for prompt engineering, multi-step orchestration, and agent behaviour design
• Ensure robust governance, including security, compliance, auditability, and responsible AI practices
• Collaborate with engineering, data, and business teams to deliver production grade AI systems
• Provide technical leadership across cloud native AI platforms, particularly within Azure ecosystems
• Mentor teams on AI architecture patterns, emerging technologies, and implementation strategies

Qualifications

• Agentic AI Frameworks
  • LangChain, LangGraph, Microsoft Agent Framework (formerly AutoGen / Semantic Kernel), CrewAI
• Databases
  • SQL databases (ideally PostgreSQL) for configuration & operational data
  • NoSQL vector databases (ideally Azure Cosmos DB) for embeddings & retrieval
• Azure Platform
  • Azure AI Foundry (agent building & orchestration)
  • Azure OpenAI Service
  • Azure AI Services
  • App Service
• AI Techniques
  • RAG architectures (chunking strategies, embedding models, retrieval pipelines)
  • Data agents with Power BI integration
• Python
  • Agent development, ML techniques, APIs
• Prompt Engineering
  • System prompt design
  • Tool/function calling patterns
  • Multi-step orchestration
• API Integration
  • Calling and orchestrating third-party APIs for agent tool use
• C#
  • API development
• DevOps
  • CI/CD pipelines (Azure DevOps or GitHub Actions)
  • Docker
  • Infrastructure as Code (Terraform or Bicep)
• Frontend Integration
  • Angular or React for agent-facing UIs or dashboards
• MCP (Model Context Protocol)
  • Tool integration with agents
  • MCP Apps (formerly MCP-UI) for interactive UI components
• Observability & Evaluation
  • LangSmith or similar tracing/evaluation tools
• Streaming & Real-Time Responses
  • SSE, WebSockets
• Testing Non-Deterministic AI Outputs
  • Evaluation strategies, golden datasets, regression testing
• Cost Management & Token Budgeting
  • Token usage, model trade-offs, caching strategies
• Multi-Agent Orchestration
  • Designing collaborative agent systems with delegation and handoffs
• Fine-Tuning / Model Customisation
  • Adapting models for domain-specific use cases
• Authentication & Identity
  • OAuth, managed identities
• Logging & Audit Trails
  • Compliance and traceability for agent decisions/actions
• Additional LLM Providers
  • Experience beyond Azure OpenAI (e.g., Anthropic, open-source via Ollama/vLLM)
• Graph Databases
  • Neo4j or similar for knowledge graph-backed agents
• Message Queues / Event-Driven Architecture
  • Azure Service Bus
• Security & Guardrails
  • Content filtering, prompt injection mitigation, PII handling
• API Design
  • REST / GraphQL for exposing agent capabilities

Benefits

• Employee-led groups such as Diversity, Equity and Inclusion committee, employee resource groups (Women and Allies), and Pride Event Group.
• Private Medical Insurance and Health Cash Plan.
• Competitive Personal Pension plan.
• Parental Leave Program.
• 25 days of annual leave plus Bank Holidays, and finish early 6 times a year with our "Flexi" scheme.
• Income Protection Plans.
• Tuition Reimbursement Schemes.
• Flexibility to work from anywhere in the world for two weeks out of the year.

EEO Statement

MRI is proud to be an inclusive employer. We welcome and celebrate diversity across all backgrounds, including ethnicity, religion, sexual orientation, gender identity, disability, age, military, veteran status and more. We believe that belonging is a direct result of diversity, equity, and inclusion. Those values are woven into the fabric of who we are and are foundational to our continued success.

We’d love to hear from you!

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