Solution Engineer

Solutions Engineer

Role Overview AI & Generative AI Architecture and Delivery

• Lead end-to-end design, development, and implementation of AI and Generative AI solutions aligned with banking industry use cases.
• Develop and deploy GenAI-powered features across both proof-of-concept initiatives and enterprise-grade banking platforms.
• Design reusable AI components and architectural frameworks to enable faster and more efficient future implementations.
• Produce and maintain detailed documentation covering all phases of the AI lifecycle, including architecture, model training, deployment, and monitoring.
• Deliver scalable, production-ready AI solutions while effectively navigating legacy system constraints.

Enterprise Systems Architecture & Integration

• Ensure all AI solutions adhere to Enterprise Architecture (EA) principles and established technology standards.
• Develop and formalize AI integration patterns that seamlessly connect with legacy infrastructure.
• Design secure, scalable deployment architectures to support organization-wide AI adoption.
• Collaborate closely with Enterprise Architecture, engineering, security, and product teams to manage dependencies and reduce integration risks.

Ethical AI, Risk & Governance

• Promote responsible AI practices, emphasizing transparency, explainability, and regulatory alignment.
• Define and implement AI governance, compliance, and risk management frameworks tailored to banking regulations.
• Monitor model performance, accuracy, and drift through dashboards, alerting systems, and continuous evaluation tools.
• Ensure regulatory, ethical, and data privacy standards are embedded throughout the AI lifecycle.

Qualifications

• Bachelor’s or Master’s degree in computer science, Artificial Intelligence, Machine Learning, Data Science, or a related field.
• Hands-on experience with Generative AI tools and frameworks such as LangChain, Hugging Face, and OpenAI APIs.
• Strong expertise in Natural Language Processing (NLP), Large Language Models (LLMs), and prompt engineering techniques.
• Proficiency in Python, with practical experience in machine learning frameworks such as PyTorch and/or TensorFlow; experience developing custom AI models is advantageous.
• Experience leveraging Microsoft AI solutions, including Azure AI Foundry, Azure Cognitive Services, and the Power Platform, for enterprise AI initiatives.
• Strong knowledge of Microsoft Azure cloud services, particularly AI deployment architectures and integration models.
• Familiarity with containerization and orchestration technologies such as Docker and Kubernetes.
• Understanding of MLOps best practices, including model lifecycle governance, monitoring, and CI/CD automation for AI systems.

Additional Requirements

• At least 3 years of professional experience in JavaScript development.
• Minimum 1 year of hands-on experience with Microsoft Azure.
• At least 2 years of practical experience in AI/ML development.

Job Types: Full-time, Permanent

Pay: RM8,000.00 - RM18,000.00 per month

Benefits:

• Health insurance
• Opportunities for promotion
• Professional development

Application Question(s):

• Are you familiar with Natural Language Processing (NLP), Large Language Models (LLMs), and prompt engineering strategies?
• Do you have experience working with Generative AI frameworks and tools such as LangChain, Hugging Face, and OpenAI APIs?

Work Location: In person