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For Companies At a Glance
- Tasks: Lead the design and delivery of AI solutions using Microsoft technologies.
- Company: Join a forward-thinking tech company in London with a hybrid work model.
- Benefits: Competitive day rate, flexible working, and opportunities for professional growth.
- Why this job: Shape the future of AI while working on exciting projects that make a difference.
- Qualifications: 10+ years in software/ML engineering with expertise in Microsoft Azure AI stack.
- Other info: Collaborative environment with a focus on innovation and responsible AI practices.
The predicted salary is between 60000 - 84000 £ per year.
AI Architect (Microsoft Tech Stack) — Contract
Location: London (Hybrid)
Contract: 6–12 months (extendable)
Start: ASAP
IR35: TBD
Day Rate: Competitive / Market rate
About the Role
We’re seeking an experienced AI Architect to lead the design, delivery, and governance of AI solutions across enterprise workloads using the Microsoft ecosystem. You’ll define AI architecture patterns, oversee solution design, guide engineering teams, and ensure alignment with security, compliance, and responsible AI standards. The role spans GenAI, ML, data platforms, MLOps, prompt engineering, and application integration.
Key Responsibilities
- Architecture & Design
- Define end-to-end AI reference architectures across data, model lifecycle, APIs, and app integrations using Azure services (Azure OpenAI, Azure ML, Azure Databricks, Azure Data Lake, Synapse/Fabric, AKS/Container Apps, Event Hub/Service Bus).
- Select and benchmark models (OpenAI, Azure AI Foundry, OSS LLMs) for task fit, cost, latency, and accuracy; design RAG and fine-tuning strategies.
- Establish MLOps / LLMOps pipelines (CI/CD, feature stores, monitoring, drift detection, human-in-the-loop).
- Delivery Leadership
- Translate business objectives into solution roadmaps, epics, and architecture runway; oversee PoCs → pilots → production.
- Provide hands-on guidance to data engineers, ML engineers, and app teams; unblock delivery and manage technical risks.
- Data & Integration
- Partner with data teams to design secure data ingestion, curation, and governance in Azure Data Lake/Fabric.
- Architect API layers (REST/GraphQL), microservices, and event-driven patterns for AI-enabled apps (including Microsoft 365/Graph integrations where relevant).
- Security, Compliance & Responsible AI
- Implement Azure security best practices: identity (Entra ID), network isolation, secrets (Key Vault), encryption, logging (Azure Monitor).
- Ensure regulatory compliance (GDPR) and responsible AI guardrails (safety filters, content moderation, auditability, model cards).
- Operational Excellence
- Define SLOs/SLAs for AI services; capacity planning, cost management (FinOps), observability, fallback strategies.
- Drive governance: model registry, prompt libraries, evaluation harnesses, data lineage, policy enforcement.
- Stakeholder Engagement
- Work closely with product, risk, and business sponsors; present architecture decisions and trade-offs to senior stakeholders.
- Contribute to standards, patterns, and playbooks; mentor teams and build community of practice.
Required Experience & Skills
- 10+ years in software/data/ML engineering with 5+ years in solution/enterprise architecture, focusing on AI/ML.
- Expert with Microsoft Azure AI stack: Azure OpenAI Service, Azure AI Foundry, Azure Machine Learning, Azure Databricks, Azure Data Lake Storage, Azure Synapse/Microsoft Fabric, Azure Kubernetes Service/Container Apps, Key Vault, Event Hub, Service Bus, API Management, App Service, Functions.
- Proven delivery of GenAI solutions (RAG, prompt engineering, tools/agents, evaluation frameworks) and ML systems (training, deployment, monitoring).
- Strong in MLOps/LLMOps: pipelines (GitHub Actions/Azure DevOps), model registry, feature store, automated evaluation, canary/blue-green deploys.
- Solid grasp of data architecture: Lakehouse, delta tables, medallion patterns, governance (Purview), performance tuning.
- Practical programming proficiency: Python (ML pipelines, SDKs), SQL, and familiarity with .NET/C# or Node/TypeScript for service integration.
- Deep understanding of security, compliance, and responsible AI principles; experience in regulated environments is a plus.
- Excellent communication and stakeholder management; able to articulate complex trade-offs to both technical and non-technical audiences.
Nice-to-Have
- Experience with Microsoft 365 Copilot extensibility, Graph connectors, and Teams integrations.
- Knowledge of vector databases (Azure AI Search, Redis, Cosmos DB, or pgvector) and embedding strategies.
- Exposure to OSS LLMs (Llama, Mistral) and hybrid architectures combining proprietary and open models.
- Industry certifications: Azure Solutions Architect Expert, Azure Data Engineer/AI Engineer, DP‑900/AI‑900.
- FinServ, Public Sector, or Healthcare domain expertise.
- Background in A/B testing, offline & online evaluation (hallucination, faithfulness, toxicity), and cost/performance optimization.
Artificial Intelligence Architect in City of London employer: Experis UK
Contact Detail:
Experis UK Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Artificial Intelligence Architect in City of London
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the AI and tech scene. Attend meetups, webinars, or even just grab a coffee with someone in the industry. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those using the Microsoft stack. This is your chance to demonstrate your expertise in Azure services and MLOps. Make it easy for potential employers to see what you can do!
✨Tip Number 3
Prepare for interviews by brushing up on common AI architecture questions. Be ready to discuss your experience with Azure OpenAI, data governance, and security best practices. Practice articulating complex concepts in simple terms – it’ll impress both technical and non-technical interviewers!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might be perfect for you. Plus, applying directly shows your enthusiasm and commitment to joining our team. Let’s get you that dream job!
We think you need these skills to ace Artificial Intelligence Architect in City of London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the AI Architect role. Highlight your experience with Microsoft Azure and any relevant projects you've worked on. We want to see how your skills align with what we're looking for!
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 your background makes you a perfect fit for this role. We love seeing enthusiasm and a personal touch.
Showcase Your Projects: If you've worked on any AI or ML projects, make sure to mention them! Include details about the technologies you used and the impact of your work. This helps us understand your hands-on experience.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you're keen to join the StudySmarter team!
How to prepare for a job interview at Experis UK
✨Know Your Tech Stack Inside Out
Make sure you’re well-versed in the Microsoft Azure AI stack. Brush up on services like Azure OpenAI, Azure ML, and Azure Databricks. Be ready to discuss how you've used these tools in past projects and how they can be applied to the role.
✨Showcase Your Architectural Skills
Prepare to talk about your experience in defining AI architecture patterns. Have examples ready that demonstrate your ability to oversee solution design and guide engineering teams, especially in relation to MLOps and data integration.
✨Communicate Clearly with Stakeholders
Practice articulating complex technical concepts in a way that non-technical stakeholders can understand. Think of scenarios where you’ve had to present architecture decisions and trade-offs, and be ready to share those experiences.
✨Emphasise Security and Compliance Knowledge
Familiarise yourself with Azure security best practices and regulatory compliance, particularly GDPR. Be prepared to discuss how you’ve implemented security measures in previous roles and how you would ensure responsible AI standards in this position.