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Aviva

AI Quality Engineering Team Lead

Aviva is hiring an AI Quality Engineering Team Lead in Warsaw, Poland. Level rates it ; you can apply on Aviva.

Level's read on this job

  • Level rates this role Works on AI ●●●○: the daily work is on AI products, without building the model.
  • The posting mentions Python, Azure DevOps and RAG among its tools and skills.
  • Level classes it as a lead role.
  • Aviva has 138 other open roles on Level.
  • Posted within the past week.

AI in this role

Lead the quality engineering approach for generative and agentic AI solutions, evaluating model behavior and reliability.

pythonazure-devops
ragai-evaluationai-safetyquality-assurancegenaitestingpython

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 Engineering Team Lead to help establish trustworthy, scalable quality engineering for GenAI and agentic AI solutions at Aviva. You will combine hands-on evaluation with team leadership, helping stakeholders understand whether AI solutions are accurate, safe, reliable and ready for release. 


This is a role for someone who can connect business risk with datasets, AI behaviour, evaluation metrics and engineering controls. You will shape reusable quality practices, challenge weak evidence and guide engineers in producing clear, auditable findings.


What will you be doing?


  • Leading the quality engineering approach for AI solutions, from risk assessment through release and monitoring.
  • Evaluating multi-turn, RAG and agentic AI behaviour, including grounding, guardrails and tool use.
  • Building representative datasets and assessing coverage, balance, leakage, label quality and freshness.
  • Assessing correctness, relevance, hallucination, safety, bias, privacy and behavioural drift.
  • Investigating unexpected outcomes across data, prompts, models, retrieval, integration, orchestration and evaluators.
  • Building reusable evaluation components, automated test pipelines, reporting and evidence-generation patterns for multiple AI products.
  • Combining test methods and validating automated evaluators against human judgement.
  • Using baselines, key metrics and risk-based regression tests to support release decisions.
  • Integrating evaluation into CI/CD, observability and engineering workflows with traceability across datasets, prompts, models and metrics.
  • Producing concise, auditable findings that explain confidence, uncertainty, customer impact and residual risk.
  • Partnering with product, engineering, architecture, data, risk, compliance and quality stakeholders to influence delivery and release decisions.
  • Coaching and guiding AI Quality Engineers, planning team work, reviewing outputs and building a collaborative culture of constructive challenge and learning.

What we're looking for:


  • Several years of relevant professional experience in quality engineering, software testing, software engineering, data science or a related technical field.
  • Hands-on experience evaluating AI, large language model, RAG or agent-based applications.
  • Practical Python skills and experience with APIs, logs, traces, structured datasets and SQL or similar 
    analysis.
  • Ability to design repeatable evaluations and automation, not just manual testing or vendor scoring.
  • Good understanding of sampling, thresholds, trends and non-deterministic system behaviour.
  • Experience with automated testing, version control, CI/CD and maintainable engineering practices.
  • Ability to turn technical findings into decision-quality evidence for business, risk and engineering stakeholders.
  • Experience coaching or leading engineers in an emerging or ambiguous domain.
  • Strong communication and influencing skills, with the confidence to challenge weak evidence.

Nice to have:


  • Experience leading projects, coordinating technical workstreams or managing people.
  • Experience with AI evaluation or observability tools such as DeepEval, Arize or similar platforms.
  • Experience designing shared frameworks, reusable services or platform capabilities.
  • Knowledge of responsible AI, model risk, controls, privacy or customer-outcome requirements.
  • Experience in financial services, insurance or another regulated industry.
  • Exposure to cloud AI systems, observability and production support.

In Aviva Services Excellence Centre, we provide:  


  • Contract of employment  
  • Performance Bonus  
  • Private medical care (ENEL-MED)  
  • Cafeteria system of benefits (e.g. MultiSport card)  
  • Additional parent privileges:  
    - baby leave – 6 weeks leave for second parent  
    - shortened working time after parental leave  
  • Employer-funded group insurance  
  • Employee Shares Plan  
  • Extra day off for birthday  
  • Paid time off to volunteer  
  • Additional leave acquired over the years in the company (even 5 days more in a year)  
  • Wellbeing Leave - additional two weeks paid leave after 10 years of service  
  • Psychological support consultations  
  • Access to the e-learning platforms  
  • Internal employee referral program  
  • Hybrid working model from Poland with a few days in Warsaw office per month
  • Attractive office location in Warsaw - Gdański Business Center  
  • Additional entitlements for people with disabilities - Work Without Barriers  
  • Work environment that promotes diversity - Diversity Charter  


Do you see yourself in Aviva Services Excellence Centre? Be sure to apply!   

Aviva is for everyone!


We’ve been ranked the #1 Best Workplace in Poland for a second year in a row and a top choice for Millennials by Great Place to Work®! 


As a signatory to the Diversity Charter, Aviva applies a policy of equal treatment and creates a work environment that is friendly to people with disabilities. We do not require from candidates the date of birth, marital status and attached photos to your CV. We encourage all individuals regardless of gender to apply.  

Most of our people are smart working – spending also time in our office - combining the benefits of flexibility, with time together with colleagues.  

We’re inclusive - we welcome applications from people with diverse backgrounds and experiences.  

Excited but not sure you tick every box? Research tells us that women, particularly, feel this way. So, regardless of gender, why not apply and try! 

To find out more about current job offers at Aviva take a look here. 


 

How we rate this

AI Quality Engineering Team Lead at Aviva rates 75 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

RAGAI EvaluationAI SafetyQuality AssuranceGenAITestingPythonAzure DevOps

Questions you could be asked

  1. How would you design a retrieval step so the model answers from real data instead of guessing?
  2. How do you decide that one model's output is better than another's for a given task?
  3. How do you think about the risk of an AI system in this kind of role failing silently?
  4. Tell me about a project where quality assurance was part of your work. What did you do?
  5. Tell me about a project where genai was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: RAG, AI Evaluation, AI Safety, Quality Assurance, and GenAI. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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