AI Finance Solution Architect
Salary: RM 10,000 – RM 12,000 per month
About the role
We are seeking an experienced AI Finance Tech Lead / Solution Architect to lead the architecture, design, and delivery of next-generation AI-powered Finance solutions for enterprise customers. This role serves as the technical leader of the Finance AI team and is responsible for defining end-to-end architecture across data, AI models, applications, integrations, and cloud platforms. The candidate will guide engineering teams, drive architecture decisions, and ensure scalable, secure, and production-ready AI solutions.
Key responsibilities
Design scalable, secure and production-ready enterprise AI solutions
Define technical approaches for LLMs, RAG, Agents, APIs and system integrations
Make key technology and architecture decisions
Guide engineers through design, development and production deployment
Ensure solution quality, security, performance, reliability and cost efficiency
Communicate technical decisions and risks to global stakeholders
About you
Three to Six (3-6) years of hands-on software engineering or solution architecture experience, including proven technical leadership in delivering production-grade LLM / Generative AI / Agent / RAG solutions
Strong understanding of LLM capabilities, limitations and architecture patterns, with practical experience in prompt engineering, RAG pipelines, tool calling, agent orchestration and model evaluation
Proven ability to design scalable, secure and maintainable enterprise AI architectures, covering APIs, data ingestion, vector databases, identity and access management, observability, deployment and integration with existing enterprise systems
Strong hands-on experience with Python and modern backend development, including REST APIs, asynchronous processing, distributed systems and cloud-native deployment
Demonstrated experience leading architecture decisions, conducting technical reviews, resolving complex engineering issues and guiding engineers from solution design through production launch and ongoing optimization
Hands-on experience collaborating with distributed, cross-functional global teams across multiple time zones, including product, engineering, data, security, compliance and business stakeholders
Fluent business English for technical discussions, architecture documentation, stakeholder communication and global meetings
Working knowledge of enterprise data privacy, security and responsible-AI requirements, including access control, data isolation, sensitive-data handling and auditability
Practical working knowledge of Jira and Confluence for technical planning, documentation, delivery tracking and cross-team collaboration