Quality Assurance

JUTEQ is an AI-native and cloud-native consulting firm helping enterprises in financial services, telecom, and healthcare build intelligent, production-grade systems. We architect and deploy GenAI platforms, build agentic workflows, and ensure our software is secure, scalable, and human-aligned.

We are hiring a Quality Assurance Engineer to help us validate the behavior, performance, and safety of our AI-powered and agentic systems across web, mobile, and LLM-driven workflows.

What You'll Do

• Design, write, and execute test cases for full-stack applications, including web UI, backend APIs, and LLM-powered agents.
• Manually test and automate regression test suites for agentic workflows and RAG pipelines.
• Validate email-based flows (XML, SMTP/IMAP) and intelligent systems that integrate with CRM, CDP, or lead management platforms.
• Design adversarial test scenarios for LLM behavior—covering hallucinations, bias, injection attacks, and prompt misalignment.
• Own QA for both deterministic flows (web, database) and probabilistic outputs (LLM responses, ranking, summarization).
• Perform API and database testing for microservices and data pipelines (PostgreSQL, MongoDB, Redis).
• Work with developers to integrate QA suites into CI/CD pipelines (GitHub Actions, Cloud Build, etc.).
• Maintain test documentation and raise detailed, reproducible bugs with logs, screenshots, and LLM outputs.

What We’re Looking For

• 2–4 years of experience in QA for web, mobile, or backend systems (manual and automation).
• Experience testing systems involving LLMs (OpenAI, Claude, Mistral), RAG workflows, or agent orchestration is highly preferred.
• Strong understanding of SDLC, STLC, and defect lifecycle management.
• Proficiency in tools like Selenium, Postman, JMeter, Pytest, or Playwright.
• Familiarity with bug tracking/project management tools: ClickUp, GitHub Projects, or JIRA.
• Exposure to prompt engineering and LLM behavior testing is a strong bonus.
• Comfortable writing SQL queries and working with data validation scenarios.
• Strong communication skills and a collaborative mindset.

Nice-to-Haves

• Understanding of CI/CD workflows and integrating QA checks into pipelines.
• Experience generating synthetic data or working with tools like Faker, Mockaroo, etc.
• Familiarity with tools like Guardrails,, or LangSmith for evaluating LLM behavior.
• Prior experience testing AI chatbots, agents, or multi-modal workflows.
• Ability to debug and test across frontend (React/Next.js), backend (Node.js/Nest), and Python-based agents.

How to Apply

Send us:

• Your resume
• (Optional) Links to GitHub, portfolio, or projects you've tested
• (Optional) A short Loom/video walking through a testing strategy you’ve implemented

Job Type: Full-time