Kerja Sepenuh Masa, Senior AI Engineer (Agentic - Generative AI) di Randstad Malaysia Federal Territory - Maukerja

Experience: 4+ Years

Technical Stack: Python, LangChain, PyTorch, Azure AI

Position Summary

We are seeking a Senior AI Engineer to design and deploy Agentic and Generative AI solutions that automate and optimize complex business processes. The successful candidate will transition innovative prototypes into scalable, production-grade applications, driving efficiency through advanced AI orchestration and autonomous system design.

Key Responsibilities

• Architectural Design: Develop and optimize RAG pipelines and multi-agent systems to facilitate autonomous decision-making and collaboration.

• Integration & Implementation: Utilize Model Context Protocol (MCP) and Python to integrate AI models with external systems and Master Data Management (MDM) platforms.

• MLOps & Deployment: Build and maintain CI/CD pipelines via Azure AI Foundry for model training, testing, and real-time performance monitoring.

• Cross-Functional Leadership: Collaborate with stakeholders to translate business requirements into technical AI use cases, including automated visual inspection and financial reporting.

• Governance: Ensure all solutions adhere to enterprise standards for security, data privacy, and Ethical AI (fairness, transparency, and traceability).
  
  

Technical Qualifications

• Programming: Mastery of Python (C# experience is a plus).

• AI Frameworks: Professional proficiency in LangChain for orchestration and PyTorch for model development/fine-tuning.

• Generative AI: Expert-level prompt engineering and experience in refining LLM performance for enterprise applications.

• Infrastructure: Proven experience deploying scalable AI solutions on cloud platforms, specifically Azure or AWS.

• Data Systems: Strong understanding of feature engineering, data management, and automated visualization techniques.
  
  

Core Competencies

• Analytical Rigor: Ability to solve complex problems with data-driven, scalable logic.

• Business Orientation: Commitment to delivering measurable ROI through process digitization.

• Communication: Proficiency in conveying technical architectures to non-technical stakeholders.

• Adaptability: Rapidly integrating emerging AI research and frameworks into existing ecosystems.