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Senior QA Engineer (Hybrid)

Velozient

São PauloFull-timeMid LevelOn-site

Job Description

  • Job Description
  • Senior QA Engineer (Hybrid)
  • We are looking for a remote, full-time Senior QA Engineer with 5+ years of experience in quality assurance testing to join and focus on our U.S. client's automation needs. Primary duties include testing all new feature enhancements, maintaining test cases and overall regression testing of the application. This key individual should have experience making decisions and working both independently and as part of a small, dynamic team where everything you do makes a difference.
  • Our client provides business-automating enterprise resource planning (ERP) software to the oil & gas industry.

    The client's software and services streamline and automate complex processes, such as revenue distribution, billing, order management, production accounting, accounts payable, contract management, and more, for over 1,700 customers across 9 countries.

  • Responsibilities
  • Create and execute test plans for existing products and features
  • Develop and execute manual as well as automated tests using Playwright MCP
  • Evaluate requirements and acceptance criteria as well as build scenarios ensuring full traceability
  • Work with development team early in the software development lifecycle to define testing strategies and protocols for new features
  • Required Experience
  • Excellent English communication and teamwork skills
  • 5+ years of experience in quality assurance automation testing, including functional, bug verification, regression, user acceptance, and user experience testing, including testing services
  • Experience using Playwright MCP
  • Strong experience with API testing and Postman
  • Experience testing REST-based services
  • Experience with project management tracking systems, such as Targetprocess
  • Excellent troubleshooting capabilities and problem-solving skills
  • Required AI Skills
  • Prompt Engineering for Test Generation: Ability to craft precise prompts that produce structured, automation-ready test cases. This includes writing clear acceptance criteria, providing domain context (ERP, oil & gas terminology, UI element names), and iterating on output quality. Familiarity with chain-of-thought prompting and few-shot examples is expected
  • AI-Assisted Test Case Review: Using LLM tools to review test cases for completeness, independence, and coverage gaps — not just accepting AI output at face value.

    The candidate must know how to validate AI suggestions against source requirements and flag hallucinations or incorrect domain assumptions

  • Feedback Loop Literacy: Understands that AI test tools learn from corrections. Can submit high-quality, structured feedback (specific field names, exact navigation paths, corrected expected results) rather than vague complaints. Recognizes that correction quality directly affects future generation quality
  • RAG and Knowledge Pipeline Awareness: Basic understanding of how retrieval-augmented generation works — why help documentation, existing test cases, and source code all contribute to AI output quality.

    Can identify when a knowledge source is missing or stale and knows how to escalate or fix it

  • Preferred AI Skills / Experience
  • Scripting with AI Assistance: Able to use AI coding assistants (GitHub Copilot, Claude Code, Codex) to write test automation scripts, validation utilities, or data prep scripts. Does not need to be a full developer, but must be comfortable reviewing and debugging AI-generated code before running it
  • AI-Powered Exploratory Testing: Uses AI to generate edge cases, boundary conditions, and negative scenarios beyond the obvious happy path. Can prompt an LLM with a feature spec and extract a prioritized list of risk areas to explore manually
  • Documentation with AI: Leverages AI to produce and maintain QA documentation — test plans, bug reports, release notes, test coverage summaries.

    Produces clean, reviewable output rather than raw AI dumps

  • Prompt-Driven Gap Analysis: Can use AI tools to compare existing test coverage against a work item backlog and identify untested or under-tested areas. Understands coverage metrics and can articulate why a gap exists, not just that one does
  • Additional Information
  • Enjoy a fun, fast-growing entrepreneurial company, and work with smart and creative people
  • Be part of a highly collaborative learning culture - share knowledge, be inclusive, learn and grow together. Embrace teamwork!
  • Knowing your ideas are heard and matter - think big!
  • Making mistakes is human - lets learn from them - be transparent!
  • We recognize you as an individual - no presumptions or judgment
  • 15 days Paid Time Off (PTO), 1 floating day, 3 sick days, and your national holidays
  • About Velozient
  • We are a privately held, nearshore software development company providing outsourced development resources to North American companies.

    Our mission is to offer development talent that enjoy taking on challenging work, want to grow their skills and experiences building software, and excel in a fast-paced, dynamic team environment. We are focused on providing world-class remote resources to work as valued client team members. If this type of opportunity excites you, then consider joining our team!

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