AI Quality Engineer

3 weeks ago

London, 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

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