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AI Quality Engineer

16 hours ago

Toronto, Ontario, Canada New York Technology Partners Full time

We are looking for a
AI Quality Engineer
with strong automation expertise and hands-on experience validating LLMs, GenAI workflows, and AI-driven applications. This role involves building automated test suites, validating AI outputs, ensuring system reliability, and contributing to the quality strategy for next-generation AI features.
Core Experience

  • 4-6 years as a Software Engineer, SDET, or Automation Engineer.
  • Strong coding skills in Python, TypeScript, or Java.
  • Hands-on experience developing automation scripts, tools, or frameworks.
  • Practical experience using LLMs, prompt engineering, and evaluating AI-generated outputs.
  • Familiarity with agentic AI systems and exposure to tools like LangGraph, AutoGen, or CrewAI.
  • Basic understanding of Model Context Protocol (MCP) or context-aware workflow automation (nice to have).

AI / ML Technologies

  • Practical experience with AI/ML frameworks:
  • LangChain, Hugging Face, GPT models, vector databases, RAG pipelines.
  • Experience with ML/DL libraries such as:
  • Scikit-learn, PyTorch, TensorFlow, Keras, Transformers, OpenCV.
  • Ability to work with embeddings, similarity search, and content evaluation metrics.

GenAI & AI Agent Development

  • Ability to integrate or build GenAI components, including RAG pipelines or agent-based workflows.
  • Support model evaluation tasks such as:
  • Output quality checks
  • Hallucination detection
  • Prompt validation
  • Regression checks for model updates

Automation & Quality Engineering

  • Experience building automation using Python, PyTest, Selenium, Playwright, or API testing libraries.
  • Ability to design and execute automated tests for:
  • Functional
  • Integration
  • API
  • Basic performance & reliability testing
  • Hands-on experience testing RESTful APIs and building automated API suites.

Cloud, DevOps & CI/CD

  • Exposure to deploying AI or automation solutions on AWS.
  • Working knowledge of CI/CD pipelines, including:
  • Automated testing
  • Model validation steps
  • Versioning & artifact management

SDLC & Collaboration

  • Strong understanding of the software development lifecycle, including requirements, development, testing, and defect analysis.
  • Ability to collaborate with Developers, Data Scientist, and QE teams, clearly communicating progress, risks, and results.
  • Skilled in documenting and tracking defects and participating in defect triage.