# AI Quality Engineer at Aviva

Aviva is hiring an AI Quality Engineer in Warsaw, Poland. Level rates it Little AI ●○○○; you can [apply on Aviva](https://jobsbylevel.com/go/9e51d385-5289-4627-9a16-a6624abe37a8?utm_medium=ai-agent).

AI Level 1, AI centrality 7 out of 100. Poland - Warsaw - ASEC.

## Details

- Company: [Aviva](https://jobsbylevel.com/companies/aviva)
- AI level: AI Level 1 (score 7 out of 100)
- Location: Poland - Warsaw - ASEC
- Posted: October 26, 2026
- Apply: https://jobsbylevel.com/go/9e51d385-5289-4627-9a16-a6624abe37a8?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=ai-quality-engineer-at-aviva-b0a2be

## Prepare for this job

The job page lists 2 likely interview questions for this offer, with a CV checklist: https://jobsbylevel.com/jobs/ai-quality-engineer-at-aviva-b0a2be

## Description

Hi, we're glad you're here! We are hiring to our Aviva Services Excellence Centre! Take a look at our job description - maybe it suits you or one of your friends? We are looking for an AI Quality Engineer to join Aviva Services Excellence Centre (ASEC) and help build confidence in the quality, safety and reliability of AI-powered products. This is a hands-on role for someone who enjoys understanding how AI systems behave, identifying weaknesses before they become customer problems, and creating reliable ways of measuring whether AI solutions are actually delivering the outcomes they were designed for. You will work across conversational AI, autonomous agents and other AI-powered systems, partnering closely with engineers, product teams and business stakeholders to ensure solutions are robust, trustworthy and ready for production use. What will you be doing? Translating business expectations, user outcomes and operational risks into measurable evaluation criteria. Defining what successful, partially successful and unsuccessful system behaviour looks like, including the gradient between clear success and clear failure. Designing evaluation approaches for conversational, multi-turn and non-deterministic AI systems. Building and maintaining representative evaluation datasets covering common, rare, boundary and high-risk scenarios. Assessing dataset quality, including coverage, class balance, duplicates, data leakage, label quality, synthetic-versus-production differences and dataset freshness. Selecting appropriate manual, deterministic, model-based and statistical evaluation methods. Analysing errors by category, user journey, risk level and likely root cause. Distinguishing model failures from failures in retrieval, chunking, ranking, prompts, tools, guardrails, integrations, source data and evaluators. Validating automated evaluators, including LLM-as-a-Judge, against human judgement. Detecting blind spots, noise, bias and misleading aggregation in evaluation results. Creating baselines, controlled comparisons and regression tests that allow meaningful comparison between system versions. Prioritising tests according to the probability and impact of failure rather than coverage alone. Communicating results, uncertainty, limitations and residual risks in a form that supports release and product decisions. Proactively identifying emerging failure modes based on system changes, production observations and research. What we're looking for: Professional experience in quality engineering, software testing, test automation, data science, software engineering or a related field (we can consider different seniority levels) . Experience or strong interest in working with AI-powered solutions, either through developing, testing, evaluating or supporting them. Good Python proficiency and experience writing clean, maintainable code for analysis, automation or testing purposes. Interest in understanding how AI systems behave, how reliable they are, and how their quality can be measured. Strong analytical and problem-solving skills, with the ability to investigate issues and identify root causes. Ability to translate business objectives, customer outcomes and risks into practical evaluation approaches. Strong communication skills and the ability to explain findings to both technical and non-technical stakeholders. A curious, proactive mindset and a genuine interest in AI, emerging technologies and system robustness. Nice to have: Experience evaluating, testing or monitoring AI-powered systems in production environments. Working with structured data, especially JSON, logs and tabular evaluation results. Understanding of LLM behaviour, tokenisation, context limits, parameters and non-determinism. Understanding of multi-turn context, RAG, grounding, faithfulness, hallucinations, guardrails, attacks (like prompt injection etc.) and tool/function calling. Software engineering practices: Git, modular code, configuration management and automated

The description is cut here. Read the full offer: https://jobsbylevel.com/jobs/ai-quality-engineer-at-aviva-b0a2be

Source: https://jobsbylevel.com/jobs/ai-quality-engineer-at-aviva-b0a2be

## Cite this page

Level. https://jobsbylevel.com/jobs/ai-quality-engineer-at-aviva-b0a2be.

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