At a Glance
- Tasks: Design and deliver next-gen AI platforms for global clients using cutting-edge technologies.
- Company: Leading enterprise AI services firm with a focus on innovation.
- Benefits: Competitive daily rate, remote work, and opportunity to mentor others.
- Other info: Exciting role with potential for career growth and impact in the AI field.
- Why this job: Join a dynamic team and shape the future of AI technology.
- Qualifications: 5+ years in software and AI/ML, with hands-on architecture experience.
The predicted salary is between 30000 - 40000 £ per year.
A leading enterprise AI services firm is looking for a hands-on AI Architect to define and deliver next-generation GenAI and agentic AI platforms across a global client base. You'll own end-to-end architecture across Azure AI Foundry, Databricks, and AWS — from discovery through production — and act as a trusted technical voice in pre-sales, CXO conversations, and partner co-innovation.
What You'll Be Doing:
- Designing reference architectures and platform standards for repeatable, scalable client delivery
- Architecting production-grade GenAI platforms on Azure AI Foundry — RAG, copilots, and multi-agent systems
- Building Lakehouse-based AI platforms using Databricks, Mosaic AI, MLflow 3.0, and Unity Catalog
- Designing multi-agent systems with LangGraph, CrewAI, AutoGen, Semantic Kernel, and Bedrock Agents
- Defining enterprise standards for MCP servers, A2A communication, and agent-to-system interoperability
- Owning Responsible AI guardrails aligned to NIST AI RMF, EU AI Act, and ISO/IEC 42001
- Mentoring architects and engineers, leading design authority forums and architecture reviews
Core Tech Stack:
- Azure AI Foundry
- Azure OpenAI
- Databricks
- Mosaic AI
- MLflow 3.0
- Amazon Bedrock
- LangGraph
- LangChain
- Semantic Kernel
- Microsoft Fabric
- Unity Catalog
- Python
- Terraform
- Kubernetes
- OpenTelemetry
What We're Looking For:
- 5+ years in software, data, and AI/ML with at least 4–5 years as a hands-on architect delivering production AI systems
- Proven delivery across at least two of: Azure AI Foundry, Databricks, AWS (all three ideal)
- Deep expertise in GenAI, agentic AI, RAG patterns, LLM fine-tuning, and vector databases
- Strong Python foundations — PyTorch, Transformers, FastAPI, LangChain/LangGraph
- Experience with MLOps, CI/CD, IaC, and container orchestration at enterprise scale
- Confident communicator — able to engage CXOs and engineering teams with equal credibility
- UK based and eligible to work in the UK
Nice to Have:
- Databricks certifications (Generative AI Engineer, Data Engineer Professional, ML Professional)
- AWS certifications (Solutions Architect Pro, ML Specialty, AI Practitioner)
- Exposure to regulated industries — BFSI, Healthcare, Pharma, Telecom
- Experience with knowledge graphs, multimodal AI, or open-source contributions in AI/ML
Interested? Send your CV and current availability to be considered for this role.
AI Architect employer: Vermillion Analytics
Join a leading enterprise AI services firm that champions innovation and collaboration in the rapidly evolving field of artificial intelligence. With a strong focus on employee growth, you will have the opportunity to mentor fellow architects and engineers while working remotely from anywhere in the UK, ensuring a flexible work-life balance. Our inclusive work culture fosters creativity and encourages you to take ownership of cutting-edge projects, making it an ideal environment for those seeking meaningful and rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land AI Architect
✨Tip Number 1
Network like a pro! Reach out to your connections in the AI field and let them know you're on the lookout for opportunities. You never know who might have a lead or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your past projects, especially those involving Azure AI Foundry or Databricks. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with both tech teams and CXOs.
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining us. Plus, it makes it easier for us to keep track of your application.
We think you need these skills to ace AI Architect
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the AI Architect role. Highlight your hands-on experience with Azure AI Foundry, Databricks, and AWS, as well as any relevant projects you've worked on.
Showcase Your Technical Skills:Don’t just list your technical skills; demonstrate them! Include specific examples of how you've used Python, MLOps, or container orchestration in your previous roles to deliver production-grade AI systems.
Communicate Clearly:Since this role involves engaging with CXOs and engineering teams, make sure your application is clear and concise. Use straightforward language to explain your experience and how it aligns with the responsibilities of the role.
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss out on any important updates!
How to prepare for a job interview at Vermillion Analytics
✨Know Your Tech Stack
Make sure you’re well-versed in the core technologies mentioned in the job description, like Azure AI Foundry, Databricks, and AWS. Brush up on your knowledge of GenAI and agentic AI platforms, as well as tools like Python and Terraform. Being able to discuss these confidently will show that you’re the right fit for the role.
✨Prepare Real-World Examples
Think of specific projects where you've designed or delivered production-grade AI systems. Be ready to explain your thought process, the challenges you faced, and how you overcame them. This will demonstrate your hands-on experience and problem-solving skills, which are crucial for an AI Architect.
✨Engage with Confidence
As a confident communicator, practice how you’ll engage with both technical teams and CXOs. Prepare to articulate complex concepts in a way that’s easy to understand. This balance is key, so consider rehearsing with a friend or colleague to refine your delivery.
✨Understand Responsible AI
Familiarise yourself with Responsible AI guardrails and frameworks like NIST AI RMF and the EU AI Act. Be prepared to discuss how you would implement these standards in your work. Showing that you prioritise ethical considerations in AI will set you apart from other candidates.
