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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, hybrid work options, and a dynamic team environment.
- Why this job: Make a real impact by delivering production-ready AI solutions in a cloud-native setting.
- Qualifications: Expertise in LLM pipelines, Azure AI stack, and strong Python skills are essential.
- Other info: This role offers a chance to collaborate with top professionals in a regulated financial environment.
The predicted salary is between 54000 - 90000 £ per year.
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.
Artificial Intelligence Engineer employer: Job Traffic
Contact Detail:
Job Traffic Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Artificial Intelligence Engineer
✨Tip Number 1
Familiarise yourself with the specific tools mentioned in the job description, such as LangChain, LlamaIndex, and Haystack. Having hands-on experience or projects showcasing your skills with these technologies can set you apart during the interview.
✨Tip Number 2
Since the role involves collaboration with cross-functional teams, be prepared to discuss your previous experiences working in team settings. Highlight any successful projects where you worked alongside data scientists or engineers to deliver solutions.
✨Tip Number 3
Brush up on your knowledge of Azure AI services, especially Azure OpenAI and Azure Search. Being able to articulate how you've used these services in past projects will demonstrate your readiness for the role.
✨Tip Number 4
Understand the regulatory environment of the financial services sector. Be ready to discuss how you have ensured compliance and security in your previous AI projects, as this is crucial for the position.
We think you need these skills to ace Artificial Intelligence Engineer
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 and MLOps tools.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company's AI transformation. Mention your hands-on experience with relevant technologies and how you can contribute to building production-ready solutions.
Showcase Relevant Projects: If you have worked on projects involving LLM pipelines or vector databases, include these in your application. Describe your role, the challenges faced, and the outcomes achieved to illustrate your capabilities.
Prepare for Technical Questions: Anticipate technical questions related to AI engineering, particularly around Azure services and security compliance. Brush up on your knowledge of embedding models and vector search architecture to impress during the interview.
How to prepare for a job interview at Job Traffic
✨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 articulate your experience with Azure OpenAI and Azure Search. Consider discussing how you've used these tools to solve real-world problems.
✨Highlight Collaboration Experience
This position involves working with cross-functional teams, so be ready to share examples of how you've collaborated with data scientists, architects, and engineers in previous roles. Emphasise your ability to communicate complex ideas clearly.
✨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.
