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AI Test Engineer
About Concept Quality Reply: Concept Quality Reply is a QA and software testing company focused on delivering high-quality digital solutions. We provide governance and production monitoring to ensure ongoing performance and compliance after release. Through advanced test automation and AI-driven testing strategies, we help organizations accelerate development, reduce risk and ensure reliability across the entire software lifecycle. Our goal is to transform QA into a strategic driver of innovation and efficiency.
Role Overview: We are looking for a mid/senior-level AI Testing & Engineering Specialist with strong Python expertise and solid experience in AI, Data Engineering, or Test Automation. The role is focused on building and evolving a next-generation testing framework for generative AI agents, including evaluation pipelines, synthetic data generation, observability layers, and quality metrics for LLM-based systems. You will work across AI engineering, data pipelines, and quality automation, contributing both to architecture design and hands-on implementation of scalable testing and evaluation systems. This role is suited for someone who can operate independently, contribute to technical decisions, and help shape standards for AI system validation in production environments.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
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No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Responsibilities: Design and develop Python-based frameworks for testing and evaluating AI agents and LLM-based systems Contribute to architecture design for evaluation pipelines, observability, and data-driven testing systems Build and maintain tools for test data generation (including synthetic and adversarial datasets) Define and implement evaluation strategies and quality KPIs for AI behavior (accuracy, robustness, bias, consistency, hallucination rate, etc.) Integrate LLM evaluation tools, CI/CD pipelines, and external AI platforms Support continuous testing, benchmarking, and production monitoring of AI systems Collaborate with AI engineers, data engineers, and QA teams to improve system reliability and scalability
About the candidate: 2–5+ years of experience in Software Engineering, Test Automation, AI Engineering, or Data Engineering Strong proficiency in Python and data/AI libraries (e.g., pandas, numpy, PyTorch or similar) Solid understanding of LLMs, NLP concepts, or generative AI systems Experience with test automation frameworks (e.g., PyTest, Playwright) and CI/CD pipelines Familiarity with data pipelines, dataset design, or feature engineering is a strong plus Experience with evaluation metrics for NLP/AI systems (BLEU, ROUGE, embedding-based metrics, or custom scoring approaches) Ability to design scalable systems and work autonomously on complex technical problems Strong analytical mindset and interest in AI system quality, reliability, and governance


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