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For Companies At a Glance
- Tasks: Join us to build cutting-edge AI solutions and optimise workflows in a hybrid role.
- Company: Be part of a major UK bank leading the charge in AI transformation.
- Benefits: Enjoy a competitive day rate and flexible hybrid working options.
- Why this job: Make an impact by delivering production-ready AI solutions in a dynamic team environment.
- Qualifications: Bring your expertise in LLM pipelines, Azure AI stack, and Python to the table.
- Other info: Ideal for those with experience in regulated environments, especially financial services.
The predicted salary is between 54000 - 90000 £ per year.
Location - London (Hybrid)
Day Rate - Up to £750
Interview process - 2 stages
We're supporting a major UK bank on its AI transformation, seeking an experienced AI Engineer to take ownership of building RAG pipelines, document processing workflows, and GenAI services. The strategic direction is set and now it's time to deliver production-ready solutions in a cloud-native Azure environment.
Role Overview
- Develop and optimise RAG pipelines using LangChain, LlamaIndex, or Haystack.
- Build ingestion workflows (OCR, chunking, embedding, semantic search) and integrate with vector databases (FAISS, Pinecone, Qdrant).
- Ensure seamless integration of GenAI services into business workflows, prioritising security, scalability, and compliance.
- Collaborate with cross-functional teams (data scientists, architects, engineers) to drive high-performance, enterprise-ready solutions.
Key Skills Required
- Expertise in LLM pipelines, embedding models, and vector search architecture.
- Strong hands-on experience with the Azure AI stack (Azure OpenAI, Azure Search).
- Proficient in Python, CI/CD, and MLOps tools (Git, Azure DevOps).
- Experience working in regulated environments, ideally within financial services.
Nice to Have
- Familiarity with PEFT (LoRA, QLoRA), privacy-preserving AI, and secure deployment.
- Experience with PromptOps, cloud security, and deploying LLM solutions in VPC environments.
Contact Detail:
twentyAI Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Artificial Intelligence Engineer (London Area)
✨Tip Number 1
Familiarise yourself with the specific tools and technologies mentioned in the job description, such as LangChain, LlamaIndex, and Azure AI stack. Having hands-on experience or projects showcasing these skills can set you apart during the interview.
✨Tip Number 2
Network with professionals in the AI field, especially those who have experience in financial services. Attend relevant meetups or webinars to gain insights and potentially get referrals that could help you land the job.
✨Tip Number 3
Prepare to discuss your previous projects involving RAG pipelines and document processing workflows. Be ready to explain your approach, challenges faced, and how you ensured compliance and security in your solutions.
✨Tip Number 4
Research the bank's current AI initiatives and challenges they might be facing. Tailoring your discussion points to align with their strategic direction will demonstrate your genuine interest and understanding of their needs.
We think you need these skills to ace Artificial Intelligence Engineer (London Area)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with RAG pipelines, document processing workflows, and the Azure AI stack. Use specific examples that demonstrate your expertise in Python, CI/CD, and MLOps tools.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Mention your hands-on experience with relevant technologies like LangChain, LlamaIndex, or Haystack, and how you can contribute to their AI transformation.
Showcase Relevant Projects: If you have worked on projects involving vector databases or GenAI services, include these in your application. Describe your role, the challenges faced, and the outcomes achieved to demonstrate your capability.
Prepare for Technical Questions: Anticipate technical questions related to LLM pipelines, embedding models, and cloud security during the interview process. Brush up on your knowledge of Azure OpenAI and be ready to discuss your problem-solving approach.
How to prepare for a job interview at twentyAI
✨Showcase Your Technical Skills
Be prepared to discuss your experience with RAG pipelines and the specific tools mentioned in the job description, such as LangChain and LlamaIndex. Bring examples of past projects where you've successfully implemented these technologies.
✨Demonstrate Cloud Proficiency
Since the role requires expertise in the Azure AI stack, make sure you can talk confidently about your experience with Azure OpenAI and Azure Search. Consider preparing a brief case study of how you've used these tools in previous roles.
✨Highlight Collaboration Experience
The job involves working with cross-functional teams, so be ready to share examples of how you've collaborated with data scientists, architects, and engineers. Emphasise your communication skills and ability to work in a team environment.
✨Understand Compliance and Security
Given the regulated nature of the financial services industry, it's crucial to demonstrate your understanding of security and compliance issues. Prepare to discuss how you've ensured these aspects in your previous projects, especially when deploying AI solutions.
