AI Engineer

AI Engineer

Full-Time 60000 - 80000 £ / year (est.) Home office (partial)
Trades Workforce Solutions

At a Glance

  • Tasks: Design and build enterprise AI platforms using Azure technologies.
  • Company: Join a forward-thinking tech company in London with a hybrid work model.
  • Benefits: Enjoy competitive salary, health benefits, 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 eager to advance their careers.

Trades Workforce Solutions

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 expertise in CI/CD and MLOps – it’s a great way to catch the eye of potential employers.

Tip Number 3

Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your experience with Azure AI services and how you've collaborated with cross-functional teams. Practice common interview questions and have examples ready that highlight your problem-solving abilities.

Tip Number 4

Don’t forget to apply through our website! We’ve got loads of opportunities that match your skills. Plus, applying directly can sometimes give you an edge, as we love seeing candidates who are proactive about their job search.

We think you need these skills to ace AI Engineer

Azure AI Services
Azure OpenAI
AI Infrastructure Engineering
Generative AI
RAG Architectures
NLP
Agentic Workflows

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 align with the role, so don’t be shy about showcasing relevant projects or achievements!

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. Be specific about your experience with CI/CD and MLOps pipelines – we love details!

Showcase Collaboration Skills:Since this role involves working closely with developers and data scientists, highlight any past experiences where you’ve successfully collaborated on projects. We value teamwork, so let us know how you’ve made an impact in cross-functional settings.

Apply Through Our Website:We encourage you to apply directly through our website for a smoother application process. It’s the best way for us to receive your application and get you one step closer to joining our innovative team!

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. Bring examples of projects where you've implemented these solutions, and be ready to explain the impact they had on the business or project outcomes.

Demonstrate CI/CD and MLOps Knowledge

Familiarise yourself with CI/CD, LLMOps, and MLOps pipelines. Be prepared to discuss how you've built and managed these pipelines in previous roles, and highlight any specific tools or frameworks you've used, like Terraform.

Communicate Effectively with Stakeholders

Since collaboration is key in this role, practice articulating your ideas clearly and concisely. Think of examples where you've successfully communicated complex technical concepts to non-technical stakeholders, as this will show your ability to bridge the gap between tech and business.