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Thales

Software QA Engineer (AIR Lab)

Thales is hiring a Software QA Engineer (AIR Lab) in Singapore, Singapore. Level rates it ; you can apply on Thales.

Level's read on this job

  • On Level's scale, this role is Works on AI ●●●○: the daily work is on AI products, without building the model.
  • Tools and skills the posting cites include Claude, Claude Code and Gen AI.
  • Level classifies it as a mid-level role.
  • Level lists 3,000+ other open roles at Thales.
  • The role was posted in the last few days.

AI in this role

Software QA engineer using generative AI as a core tool to design and maintain automated integration and regression tests for lab applications.

claudeclaude-codegen-aiautomated-testing
prompt-engineeringsoftware-qatest-automationintegration-testingpipeline-management
Location: Singapore, Singapore

Thales is a global technology leader trusted by governments, institutions, and enterprises to tackle their most demanding challenges. From quantum applications and artificial intelligence to cybersecurity and 6G innovation, our solutions empower critical decisions rooted in human intelligence. Operating at the forefront of aerospace and space, cybersecurity and digital identity, we’re driven by a mission to build a future we can all trust.

In Singapore, Thales has been a trusted partner since 1973, originally focused on aerospace activities in the Asia-Pacific region. With 2,000 employees across three local sites, we deliver cutting-edge solutions across aerospace (including air traffic management), defence and security, and digital identity and cybersecurity sectors. Together, we’re shaping the future by enabling customers to make pivotal decisions that safeguard communities and power progress.

The Software QA Engineer applies sound software-engineering QA principles to AIR Lab applications, using Gen AI as a core part of the daily toolkit to design, generate and maintain automated integration, sanity and regression tests. The role is hands-on: turning a deep understanding of each product into executable tests that run in delivery pipelines and give the team fast, trustworthy feedback.

Equally important is judgement. Not every change needs the full suite, and not every proof of concept needs production-grade quality gates. This role decides, together with the Validation Lead and Product Owners, which tests are enforced as blocking gates, which run on a schedule, and where lighter-weight checks are enough, balancing confidence against delivery speed across POCs, MVPs and more mature products.

The role reports to the Head of Engineering and works closely with Product Owners/Functional Leads to understand each product, its users, and how AIR Lab applications talk to one another.

Responsibilities:

  • Work closely with Product Owners/Functional Leads to understand product intent, User Journeys, and the ATM operational context behind each application.
  • Build and maintain a clear picture of how AIR Lab products interact (interfaces, data flows and dependencies) and use it to pinpoint integration risk.
  • Design and implement automated integration tests that verify the contracts and data exchanged between applications and services.
  • Build and maintain sanity (smoke) suites that quickly confirm a deployment or environment is healthy before deeper testing begins.
  • Build and maintain regression suites that protect agreed User Journeys and previously fixed defects.
  • Use AI tools such as Claude to accelerate test work: deriving test cases from User Journeys and specifications, generating test code and test data, and analysing failures and logs.
  • Review and verify all AI-generated tests and outputs for correctness, relevance and maintainability before they are committed. AI speeds up the work; the engineer owns the quality.
  • Apply a risk-based approach to decide when tests are enforced as blocking gates (merge request, promotion to Demo/Public environments), when they run as non-blocking or scheduled checks, and when lighter verification is sufficient, based on product maturity, change impact and criticality.
  • Integrate test suites into GitLab CI/CD pipelines and ephemeral namespace environments, keeping execution time short and flakiness under control.
  • Triage test failures, separate genuine defects from test or environment issues, and raise clear, reproducible defect reports; follow up until resolution.
  • Keep test suites lean and maintainable: retire obsolete tests, fix or quarantine flaky ones, and refactor as products evolve.
  • Contribute reusable prompts, patterns and guidelines for AI-assisted testing so the wider engineering team can adopt them.
  • Report coverage, results and quality risks to the Validation Lead and Product Owners in a clear, actionable format, raising blockers early.
  • Own and drive the Software QA lifecycle, raise bugs and ensure quality of the products.

 

Requirements:

 

Education

·       Bachelor’s degree in Computer Science, Information Technology or a related engineering field

·       Master’s degree in Computer Science or a related field is a plus

 

Essential Skills/Experience

  • 4–6 years of experience in software QA or test automation, with hands-on delivery of integration, sanity and regression suites.
  • Solid grasp of software-engineering QA principles: the test pyramid, risk-based testing, test design techniques.
  • Hands-on API and service-level test automation (e.g., Karate, Pytest, REST Assured, Postman/Newman) and working proficiency in at least one programming language such as Python or Java.
  • Experience integrating automated tests into CI/CD pipelines (GitLab CI preferred) and working with containerised environments (Docker, Kubernetes).
  • Ability to understand distributed systems (APIs, messaging, data pipelines) and reason about how components interact and fail.
  • Good communication skills in English, and confidence working with product and functional stakeholders.

 

Desirable Skills/Experience

  • Exposure to the ATM/ATC or wider aviation domain.
  • Experience with prompt engineering or agentic AI workflows for engineering tasks (e.g., Claude Code), including building reusable prompts for the team.
  • Familiarity with UI or performance test automation (e.g., Playwright, Cypress, k6).
  • Experience in R&D, POC or MVP environments where test rigour is matched to product maturity.
  • Practical experience using AI assistants (e.g., Claude) to generate, refactor and analyse tests, with the judgement to verify and correct their output.

 

 

Essential / Desirable Traits

·       Pragmatic: knows when “good enough” is right and when to hold the line on quality

·       Possess learning agility, curiosity, flexibility and pro-activity

·       Collaborative and comfortable with agile teamwork and user engagement

·       Communicates risk clearly and calmly, without alarmism

 

 

YOUR CAREER AT THALES

Future opportunities will allow you to discover other domains or sites. You will be able to evolve and grow your competencies in different areas:

 

  • Room and attention to personal development
  • Build your talents in another domain of Thales Group, discovering new products, new customers, new country or go to a more complex Solution.
  • Choose between a technical expertise or a leadership path
  • Build an international career within a leading Engineering Group

At Thales, we’re committed to fostering a workplace where respect, trust, collaboration, and passion drive everything we do. Here, you’ll feel empowered to bring your best self, thrive in a supportive culture, and love the work you do. Join us, and be part of a team reimagining technology to create solutions that truly make a difference – for a safer, greener, and more inclusive world.

How we rate this

Software QA Engineer (AIR Lab) at Thales rates 60 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

Prompt engineeringSoftware QaTest AutomationIntegration TestingPipeline ManagementClaudeClaude CodeGen AI

Questions you could be asked

  1. How do you structure and test a prompt to get consistent output from a language model?
  2. Tell me about a project where software qa was part of your work. What did you do?
  3. Tell me about a project where test automation was part of your work. What did you do?
  4. Tell me about a project where integration testing was part of your work. What did you do?
  5. Tell me about a project where pipeline management was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: Prompt engineering, Software Qa, Test Automation, Integration Testing, and Pipeline Management. 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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