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- 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.
- 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
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 - AI (Contract) employer: Tec Partners
Contact Detail:
Tec Partners Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quality Engineer - AI (Contract)
✨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 yet.
✨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! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Quality Engineer - AI (Contract)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Quality Engineer role. Highlight your Python development experience and any work you've done with AI systems. We want to see how your skills match what we're looking for!
Showcase Your Experience: In your application, don't just list your previous jobs. Share specific examples of projects where you implemented evaluation frameworks or automated testing. This helps us understand your hands-on experience in regulated environments.
Be Clear and Concise: When writing your application, keep it clear and to the point. Use bullet points for key achievements and avoid jargon unless it's relevant. We appreciate straightforward communication that gets to the heart of your qualifications!
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 the role. Plus, it’s super easy to do!
How to prepare for a job interview at Tec Partners
✨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 hallucinations or latency in past projects. This will show that you understand the technical challenges and can contribute effectively.
✨Showcase Your Python Skills
Since strong Python development experience is essential, prepare to demonstrate your expertise in automation and test frameworks. Bring examples of your previous work, especially any automated testing pipelines you've developed, to highlight your hands-on experience.
✨Understand the Governance Landscape
Familiarise yourself with governance, audit, and security requirements relevant to AI systems. Be prepared to discuss how you've assessed technical solutions against these standards in your previous roles. This will show that you can navigate the complexities of a regulated environment.
✨Collaborate Like a Pro
This role involves working closely with ML Engineers and platform teams, so be ready to talk about your collaborative experiences. Share specific examples of how you've embedded testability into AI services and contributed to quality assurance strategies in team settings.