QA Azure AI Engineer

3.0

Job Type   /   Job Level

Full-time   /   Others/Any

Company Location

Malaysia

EDV Werke is looking for a QA Azure AI Engineer

Working Model: On-site, Kuala Lumpur

Form of cooperation: B2B Contract

Tasks

Generative AI Development – Build and implement AI solutions using generative models and RAG pipelines.
Cloud AI Deployment – Deploy, manage, and maintain AI models on cloud platforms with scalable architecture.
Python Engineering – Write complex Python scripts for data processing, testing, and model automation.
QA & Evaluation – Evaluate models using advanced metrics, including LLM-as-a-Judge and deterministic assertions.
DataOps & CI/CD Pipelines – Develop automated pipelines for AI testing and deployment on cloud platforms.
Technical Leadership – Provide guidance on AI model architecture and best practices for deployment.
Cross-team Collaboration – Work with data, backend, and product teams to integrate AI solutions into production.
Documentation & Reporting – Maintain reproducible workflows, technical documentation, and experiment results.

Must-Have Skills

Generative AI Expertise – 1–2 years hands-on experience with generative AI and RAG architecture (vector search + LLM).
Cloud Platform Experience – 5+ years deploying AI models on cloud AI services, not just locally.
Python Specialist – 7+ years coding in Python, including complex scripting (Pandas, PyTest) beyond basic automation.
QA & Automation Knowledge – 8+ years QA experience with LLM evaluation and test automation.
DataOps & CI/CD – 5+ years building pipelines for automated AI model testing and deployment.
Technical Degree – Degree in CS, Engineering, Math, or equivalent heavy experience.
Azure AI Deployment – Practical experience deploying and managing AI models in cloud AI services.
Evaluation Metrics Mastery – Ability to design and interpret advanced AI evaluation metrics and regression testing.

Should-Have Skills

Agentic AI / Multi-Agent Systems – Experience with agentic AI frameworks or multi-agent AI systems.
Cloud Search Expertise – Experience with cloud AI search services, including indexing, vector profiles, and hybrid search.
Python AI Frameworks – Experience using LangChain or Semantic Kernel for AI test harnesses.
Evaluation Pipelines – Experience using prompt flow to build model evaluation pipelines.
Golden Dataset Creation – Knowledge of creating ground truth datasets for regression testing.
Master’s Degree – Advanced degree in Data Science or AI-related field.

Nice To Have

Small Model Fine-Tuning – Experience fine-tuning small language models like Phi-3 or LLaMA.
Cloud ML Tools – Experience managing ML workspaces, compute instances, and experiment tracking.
Backend Integration Skills – Background in C# / .NET for AI integration with backend systems.
Security Testing – Experience with red-teaming, adversarial, or jailbreak testing for AI models.

Benefits

Jobs in Malaysia » Jobs in Kuala Lumpur, Federal Territory of Kuala Lumpur, Malaysia » QA Azure AI Engineer

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