At a Glance
- Tasks: Lead enterprise AI strategy and design scalable, cloud-native AI solutions.
- Company: Join a forward-thinking tech company focused on innovative AI solutions.
- Benefits: Enjoy hybrid work, generous leave, private medical insurance, and tuition reimbursement.
- Other info: Flexible working options and excellent career growth opportunities await you.
- Why this job: Shape the future of AI while collaborating with diverse teams and technologies.
- Qualifications: Experience in agentic AI frameworks, cloud platforms, and system integration required.
The predicted salary is between 80000 - 100000 £ per year.
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. The role focuses on agentic AI, multi‑agent systems, RAG architectures, and enterprise AI integration aligned to business goals. It establishes best practices for AI architecture, orchestration, governance, and responsible AI, partnering with cross‑functional teams to deliver secure, production‑grade solutions across the organisation. The working model is hybrid: 3 days working from home per week, based in the London office, open to UK remote candidates.
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
Must Have Skills & Experience
- Agentic AI Frameworks: LangChain, LangGraph, Microsoft Agent Framework (formerly AutoGen / Semantic Kernel), CrewAI
- Databases: SQL (e.g., PostgreSQL) for configuration & operational data; NoSQL vector databases (e.g., Azure Cosmos DB) for embeddings & retrieval
- Azure Platform: Azure AI Foundry, Azure OpenAI Service, Azure AI Services, Azure App Service, Azure AI Technologies
- RAG Architectures: chunking strategies, embedding models, retrieval pipelines
- Python for 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
- Knowledge of C# API development and 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) integration; MCP Apps 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, caching strategies
- Multi‑agent orchestration: collaborative agent systems with delegation and handoffs
- Fine‑tuning / model customization for domain‑specific use cases
- Authentication & identity: OAuth, managed identities; logging & audit trails for compliance and traceability
- Experience with additional LLM providers 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 or GraphQL for exposing agent capabilities
Benefits
- Hybrid working model – 3 days from home per week, based in London office (remote accepted within UK)
- 25 days of annual leave plus bank holidays; 6 early‑finish days per year as part of Flexi scheme
- Private medical insurance and health cash plan for employees and families
- Competitive personal pension plan and tuition reimbursement schemes
- Income protection plans and generous parental leave and support perks
- Flexibility to work from anywhere in the world for two weeks a year
Senior Enterprise Architect (AI Focused) in London employer: MRI India
Join a forward-thinking company that prioritises innovation and employee well-being, offering a hybrid working model that allows for flexibility and work-life balance. With a strong focus on professional development, you will have access to mentorship opportunities and tuition reimbursement schemes, ensuring your growth in the rapidly evolving field of AI. Located in London, our vibrant office culture fosters collaboration and creativity, making it an ideal environment for those looking to make a meaningful impact in enterprise AI solutions.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Enterprise Architect (AI Focused) in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your AI projects and architecture designs. This gives you a chance to demonstrate your expertise and passion for the role, making you stand out from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common questions related to AI architecture and multi-agent systems. Practice articulating your thought process and how you align AI strategies with business goals – it’s all about showing you can lead effectively!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive and engaged with our platform.
We think you need these skills to ace Senior Enterprise Architect (AI Focused) in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to highlight your experience with AI architectures and frameworks. We want to see how your skills align with our needs, so don’t be shy about showcasing your relevant projects!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about AI and how you can contribute to our enterprise AI strategy. Keep it engaging and personal – we love to see your personality come through.
Showcase Your Technical Skills:Don’t forget to highlight your technical expertise in areas like Azure, Python, and multi-agent systems. We’re looking for someone who can hit the ground running, so make sure we can easily spot your relevant skills!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy – just a few clicks and you’re done!
How to prepare for a job interview at MRI India
✨Know Your AI Frameworks
Make sure you’re well-versed in the agentic AI frameworks mentioned in the job description, like LangChain and Microsoft Agent Framework. Be ready to discuss how you've used these tools in past projects and how they can align with the company's goals.
✨Showcase Your Architectural Skills
Prepare to talk about your experience designing scalable AI architectures and multi-agent systems. Bring examples of past projects where you’ve implemented RAG architectures or data pipelines, and be ready to explain your thought process behind those designs.
✨Demonstrate Cross-Functional Collaboration
This role requires working with various teams, so highlight your experience collaborating with engineering, data, and business teams. Share specific instances where your teamwork led to successful AI solutions, focusing on how you navigated challenges together.
✨Be Ready for Technical Questions
Expect technical questions related to Azure platforms, API integration, and prompt engineering. Brush up on your knowledge of Python, SQL, and any relevant DevOps practices. Practising coding problems or system design scenarios can help you feel more confident during the interview.
