At a Glance
- Tasks: Design and build enterprise AI platforms using Azure technologies.
- Company: Join a forward-thinking company focused on innovative AI solutions.
- Benefits: Enjoy competitive pay, hybrid work, and opportunities for professional growth.
- Other info: Collaborate with diverse teams in a dynamic, innovation-driven environment.
- Why this job: Make a real impact by turning AI concepts into scalable solutions.
- Qualifications: Experience with Azure AI services and Generative AI is essential.
The predicted salary is between 60000 - 80000 £ per year.
Vivo Talent are looking for an experienced AI Engineer to join our client and design, build and support enterprise AI platforms and solutions within a modern Azure environment. You’ll be collaborating closely with developers, data scientists and business stakeholders to turn AI proof-of-concepts into secure, scalable production solutions. It is a great opportunity for someone looking to take concepts to solutions and make valuable impact.
Key Responsibilities
- Build and maintain AI infrastructure using Microsoft Azure technologies including Azure AI Foundry, Azure OpenAI, Azure ML and Copilot Studio.
- Develop and manage CI/CD, LLMOps, and MLOps pipelines for Generative AI applications.
- Design and deploy GenAI, RAG and intelligent agent solutions across enterprise systems.
- Implement Infrastructure as Code (Terraform) and secure cloud environments following best practices.
- Support AI experimentation, model fine-tuning, prompt evaluation and production deployment.
- Monitor AI performance, token usage, cost optimisation, reliability and security.
- Collaborate with cross-functional teams to deliver scalable and compliant AI solutions.
- Promote Responsible AI, governance, and data security across all AI initiatives.
Required Experience
- Strong experience with Azure AI services, Azure OpenAI and AI infrastructure engineering.
- Hands‑on expertise with Generative AI, RAG architectures, NLP and agentic workflows.
- Experience building secure CI/CD, LLMOps, and MLOps pipelines.
- Knowledge of Terraform, cloud security, APIs, and enterprise integrations.
- Familiarity with frameworks such as LangChain or Semantic Kernel.
- Strong stakeholder communication and cross-functional collaboration skills.
This is an exciting opportunity to help shape and scale enterprise AI capabilities while working with cutting‑edge Generative AI technologies in a secure, innovation-driven environment.
AI Engineer employer: Trades Workforce Solutions
Join a forward-thinking company that prioritises innovation and collaboration, offering AI Engineers the chance to work with cutting-edge Generative AI technologies in a hybrid environment in London. With a strong focus on employee growth, you will have access to continuous learning opportunities and the chance to make a meaningful impact by turning AI concepts into scalable solutions. The supportive work culture fosters teamwork and promotes responsible AI practices, making it an excellent place for professionals looking to advance their careers.
Contact Details:
Trades Workforce Solutions Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land AI Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the AI field, especially those working with Azure and Generative AI. Attend meetups or webinars, and don’t be shy about asking for informational interviews – you never know where a chat might lead!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to AI infrastructure and Generative AI. Use platforms like GitHub to share your code and demonstrate your hands-on expertise with Azure technologies.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your experience with CI/CD, MLOps, and how you've collaborated with cross-functional teams. Practice common interview questions to boost your confidence!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that match your skills. Plus, it’s a great way to get noticed by recruiters who are looking for talent just like you!
We think you need these skills to ace AI Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with Azure AI services and Generative AI. We want to see how your skills match the job description, so don’t be shy about showcasing 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 team. We love seeing enthusiasm and a clear understanding of the role.
Showcase Your Projects:If you've worked on any AI projects, especially those involving CI/CD or MLOps pipelines, make sure to mention them. We’re keen to see real-world applications of your skills, so include links or descriptions!
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 this exciting opportunity. Don’t miss out!
How to prepare for a job interview at Trades Workforce Solutions
✨Know Your Azure Inside Out
Make sure you brush up on your knowledge of Azure AI services, especially Azure OpenAI and Azure ML. Be ready to discuss how you've used these technologies in past projects, as well as any challenges you faced and how you overcame them.
✨Showcase Your Generative AI Expertise
Prepare to talk about your hands-on experience with Generative AI and RAG architectures. Have specific examples ready that demonstrate your ability to design and deploy intelligent agent solutions, as this will show your potential employer that you can hit the ground running.
✨Highlight Collaboration Skills
Since you'll be working closely with developers, data scientists, and business stakeholders, it's crucial to showcase your communication and collaboration skills. Think of instances where you successfully worked in cross-functional teams and how you contributed to delivering scalable AI solutions.
✨Emphasise Responsible AI Practices
Be prepared to discuss your understanding of Responsible AI and data security. Share your thoughts on governance in AI initiatives and how you've implemented best practices in previous roles to ensure compliance and security in AI projects.
