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Brasil
Remote only
At CI&T, we help large enterprises transform the potential of AI into real business impact with AI Deployment, AI-native execution, and tech-integrated business solutions.
With 30 years of experience in technological transformation, we accelerate innovation with expertise in Agentic SDLC, Application modernization, Data & AI, Martech and Business strategy.
We are 8,000 CI&Ters across more than 25 countries, collaborating to build solutions with real impact. AI is already part of how we work, evolve, and innovate every day.
We are looking for a Tester Senior/Master — the technical reference for software quality on our teams.
This role is about owning the quality strategy end to end: defining how a product should be tested, building automation, investigating the root cause of defects, and raising the technical bar across the testing team.
You will also use AI assistants and agentic workflows to design, generate, and maintain tests, helping define how quality is assured when AI is part of the software development lifecycle.
Define test strategies and plans based on business and technical requirements.
Design and execute functional, exploratory, regression, performance, and security testing as needed.
Build and maintain automated test suites to increase coverage and reduce cycle time.
Investigate root causes of defects and work with development teams to reduce defect rates.
Define and track quality metrics and drive continuous improvement through practices such as PDCA.
Use AI assistants and agents to generate test scenarios, expand coverage, refactor suites, and accelerate maintenance.
Design agentic testing workflows, applying prompt and context engineering and critically validating AI-generated outputs.
Define how quality should be assured for AI-assisted delivery.
Mentor testers, conduct technical reviews, and promote quality practices across squads.
Communicate quality metrics, plans, and status to CI&T and the client.
Solid hands-on experience in software testing.
Strong test automation skills and experience with testing frameworks and tools.
Experience with root cause analysis and defect reduction.
Experience defining and tracking quality metrics and improvement cycles such as PDCA.
Hands-on use of AI tools in real delivery work, such as AI coding assistants, LLM-based test generation, or AI-supported analysis.
Working knowledge of agentic workflows, including task structuring, context definition, chaining steps, and output validation.
Practical prompt and context engineering skills.
Critical judgment when reviewing AI-generated tests and code.
Experience working directly with clients and stakeholders.
Experience mentoring testers.
English proficiency for day-to-day work with international teams.
Experience with agentic SDLC or spec-driven development.
Familiarity with MCP servers, tool calling, or multi-agent orchestration.
Experience evaluating the quality of AI-generated artifacts.
Experience testing AI-powered products, including non-deterministic behavior, hallucination risks, and model regressions.
Performance and security testing background.
CI/CD and continuous delivery experience.
Experience with Agile or scaled Agile environments, such as SAFe.
