Generative AI Solution Architect [up to RM 20k]
Summary
Design and deploy enterprise-grade generative AI solutions on Azure, building RAG pipelines and fine-tuning LLMs with PyTorch/TensorFlow for a financial services client.
- 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.
experience
6 years
skills
generative AI, LangChain, NLP, LLM, Azure AI Foundry
qualifications
no additional qualifications required
education
Vocational/Professional Qualification
