At a Glance
- Tasks: Define evaluation frameworks and develop automated test pipelines for AI services.
- Company: Global organisation leading in AI platform engineering.
- Benefits: Competitive daily rate, hybrid work model, and exposure to cutting-edge AI technologies.
- Other info: Collaborative team environment with opportunities for professional growth.
- Why this job: Join a transformative AI initiative and shape the future of enterprise AI capabilities.
- Qualifications: Strong Python skills and experience with automated testing in regulated environments.
A global organisation is building a centralised AI enablement and platform engineering function focused on delivering scalable, secure, and governed AI capabilities across the enterprise. This role sits within a programme delivering enterprise-grade agentic AI infrastructure, including internal AI assistants, retrieval and search services, extensibility frameworks, and governance tooling.
The programme is focused on delivering a production-grade internal agentic AI platform, including:
- Development of an enterprise AI assistant capable of reasoning, planning, and tool orchestration
- Operation of enterprise retrieval, search, and grounding services for approved data sources
- Delivery of a secure internal gateway layer providing discovery, observability, policy enforcement, and lifecycle management for AI-integrated services
- Design and development of AI-integrated services and reusable capabilities that safely expose internal and third-party systems to AI agents
- Establishment of evaluation, governance, and quality-control frameworks to support scalable and compliant deployment of AI capabilities
The programme currently follows a centrally delivered model while evolving towards a federated contribution approach over time.
Key Responsibilities
- Define and implement evaluation frameworks covering correctness, safety, reliability, and regression impact for AI-integrated services
- Develop and maintain automated test pipelines for agentic workflows, including tool orchestration and multi-step execution paths
- Identify, evaluate, and mitigate AI system failure modes such as hallucinations, invalid inputs, latency issues, and inappropriate tool usage
- Produce testing and governance evidence required for internal approval and operational processes
- Collaborate closely with ML Engineers and platform teams to embed testability and evaluation capabilities into AI services
- Contribute to the long-term quality assurance and governance strategy for enterprise-wide AI platform adoption
Essential Skills and Experience
- Strong Python development experience, particularly for automation and test frameworks
- Experience with LLM and RAG evaluation tooling, frameworks, or custom evaluation pipelines
- Expertise in automated testing across unit, integration, and regression testing environments
- Good understanding of agentic AI systems, associated risks, and operational failure modes
- Ability to assess technical solutions against governance, audit, and security requirements
- Experience working within regulated or highly governed engineering environments
What’s on Offer
- Opportunity to contribute to large-scale enterprise AI transformation initiatives
- Exposure to cutting-edge AI platform engineering and governance challenges
- Collaborative environment working alongside platform engineers, ML specialists, and architecture teams
- Influence over the development of long-term AI quality and governance standards
- Opportunity to shape scalable AI engineering practices within a complex enterprise environment
Quality Engineer - Corporate Engineering AI employer: Trades Workforce Solutions
As a Quality Engineer in Corporate Engineering AI, you will join a global organisation renowned for its commitment to innovation and excellence in AI technology. With a hybrid work model based in Central London, you will benefit from a collaborative culture that fosters professional growth and offers exposure to cutting-edge AI challenges. The company prioritises employee development, providing opportunities to influence long-term quality standards and engage in large-scale enterprise transformations, making it an exceptional employer for those seeking meaningful and rewarding work.
Contact Details:
Trades Workforce Solutions Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Quality Engineer - Corporate Engineering AI
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and engineering space on LinkedIn or at industry events. A friendly chat can sometimes lead to opportunities that aren’t even advertised.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your Python projects, especially those related to automation and testing. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on common quality engineering scenarios, especially around AI systems. Think about how you’d tackle issues like hallucinations or latency problems—be ready to share your thought process!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got some fantastic roles waiting for you, and applying directly can sometimes give you an edge over other candidates.
We think you need these skills to ace Quality Engineer - Corporate Engineering AI
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the Quality Engineer role. Highlight your Python development experience and any work with AI systems to catch our eye!
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about AI and quality engineering. Share specific examples of your past work that align with the responsibilities listed in the job description.
Showcase Your Technical Skills:Don’t forget to mention your expertise in automated testing and any experience with LLM and RAG evaluation tooling. We want to see how you can contribute to our AI platform engineering efforts!
Apply Through Our Website:For the best chance of getting noticed, apply directly through our website. It’s the easiest way for us to keep track of your application and ensure it reaches the right people!
How to prepare for a job interview at Trades Workforce Solutions
✨Know Your AI Stuff
Make sure you brush up on your knowledge of agentic AI systems and their associated risks. Be ready to discuss how you've tackled issues like latency or invalid inputs in past projects. This shows you're not just familiar with the theory but have practical experience too.
✨Showcase Your Python Skills
Since strong Python development experience is essential, prepare to demonstrate your coding skills. Bring examples of automation and test frameworks you've developed. You might even be asked to solve a coding challenge during the interview, so practice those Python problems!
✨Understand Evaluation Frameworks
Familiarise yourself with evaluation frameworks for AI-integrated services. Be prepared to explain how you would define and implement these frameworks, focusing on correctness, safety, and reliability. This will show that you can contribute to the quality assurance strategy effectively.
✨Collaborate Like a Pro
This role involves working closely with ML Engineers and platform teams, so highlight your collaborative experiences. Share examples of how you've successfully worked in cross-functional teams to embed testability into AI services. It’s all about showing you can communicate and work well with others!
