generative ai solution architect [up to rm 20k].

• Career Growth Opportunities
• Excellent Benefits
• Public Transport Accessible Location

about the company

Randstad has partnered with a growing financial services organisation in Malaysia, offering a large range of products and solutions to their clientele. Your future employers have a steady reputation across the region for modern tech implementations that prioritize security, reliability and user experience across their platforms.

key responsibilities:

• End-to-End Architecture: Design, build, and deploy enterprise-grade Generative AI solutions, managing the entire lifecycle from concept and prototyping to production and monitoring.
• Azure Integration: Architect cloud-native AI solutions utilizing Microsoft Azure. Leverage Azure AI Foundry (Azure OpenAI, Azure Machine Learning) to host, deploy, and scale LLMs efficiently.
• Orchestration & Pipelines: Develop robust, secure Retrieval-Augmented Generation (RAG) pipelines and complex multi-agent workflows using LangChain.
• Custom Model Development: Utilize deep learning frameworks such as PyTorch or TensorFlow to build, train, and fine-tune specialized machine learning models when foundational LLMs require domain-specific adaptation.
• Security & Governance: Implement enterprise guardrails for AI applications, ensuring data privacy, regulatory compliance, and protection against prompt injection and data leakage.
• Cross-Functional Leadership: Collaborate closely with data engineers, DevOps, and product teams to seamlessly integrate GenAI capabilities into existing software ecosystems.

requirements:

• Experience: Minimum of 6 years of professional experience in Software Engineering, Cloud Architecture, Data Science, or Machine Learning.
• Cloud Platform: Deep, hands-on expertise with Microsoft Azure cloud infrastructure. Ability to design scalable and cost-effective AI architectures.
• AI Platforms: Proven experience working with Azure AI Foundry for building and managing AI models and copilots.
• GenAI Tools: Extensive practical experience with LangChain for LLM orchestration and workflow design.
• Machine Learning: Proficiency in classical ML and Deep Learning, with strong hands-on skills in PyTorch or TensorFlow.
• Programming: Advanced proficiency in Python.
• System Design: Strong understanding of distributed systems, APIs, microservices, and containerization (Docker/Kubernetes).

nice to haves:

• Experience with Vector Databases (e.g., Azure AI Search, Pinecone, Qdrant).
• Knowledge of MLOps / LLMOps practices (e.g., MLflow, Prompt flow).
• Experience with other orchestration tools like LlamaIndex or Microsoft Semantic Kernel.

how to apply

Kindly click on the applicable link to apply if you are interested and suitable for this role. Alternatively, you can reach out to me via LinkedIn for a confidential discussion.

Sundar Ravindran | Randstad