Senior AI QE Engineer

13 hours ago


New Canada NS NLB Services Full time

Job Role: Senior AI QE Engineer Location : West Palm Beach, Florida (Onsite) Full Time Job Description: Role Summary We are looking for a Senior 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 6–10 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 integration 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 integrations 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.


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