Senior Software Engineer – AI Solutions

CIMB; Kuala Lumpur; On-site; MYR 180,000 - 240,000; Full time

Job summary

CIMB in Kuala Lumpur is seeking a Senior Software Engineer to design and deliver enterprise-grade AI solutions for banking domains. You will work on conversational AI, RAG platforms, AI agents, document processing, workflow automation, and enterprise integrations.

Collaborating with Solution Architects and Tech Leads, you will build scalable, secure, production-ready applications leveraging cloud and AI technologies, with a strong focus on security, CI/CD, and observability.

Qualifications

• Bachelor’s Degree in Computer Science / Information Technology or equivalent.
• Minimum 5 years of professional software engineering experience, including delivery and support of production applications.
• At least 2 years of hands-on experience with Generative AI, RAG, machine learning or intelligent automation.
• Strong hands-on proficiency in Python. Experience with Java and Node.js for enterprise integration is desirable.
• Experience with modern web development using React, Vue.js or Angular.
• Strong understanding of application architecture, object-oriented programming, design patterns, RESTful APIs and microservices.
• Hands-on experience with SQL, NoSQL and vector databases, Git-based development, automated testing, Docker, Kubernetes or containerized development, CI/CD and Agile delivery.
• Practical experience with RAG pipelines, AI agents, LLM orchestration frameworks, LLM evaluation, observability, security controls and production troubleshooting is highly desirable.
• Core engineering: advanced Python, backend development, API and microservice design, clean code, automated testing and code review; Java or Node.js is beneficial.
• RAG and data: ingestion, OCR and parsing, chunking, embeddings, metadata, vector indexing, hybrid retrieval, reranking, citations and document-level access control.
• Agentic AI and LLMOps tool or MCP integration, orchestration, prompt and configuration versioning, evaluation, deployment, rollback, tracing and human-in-the-loop controls.
• Platform and reliability: cloud services, Docker, Kubernetes, CI/CD, observability, token and cost monitoring, performance optimisation, resilience and production support.
• Security and integration: OAuth2, OpenID Connect, SAML, Microsoft Entra ID, secure SDLC, sensitive-data protection, AI threat controls, event-driven architecture and enterprise API integration.
• Behavioral: ownership, analytical problem solving, attention to detail, clear communication, stakeholder collaboration, continuous learning and focus on measurable business outcomes.

Responsibilities

• Translate approved business use cases and solution designs into secure, scalable and maintainable enterprise applications.
• Develop backend services, microservices, RESTful APIs and, where required, responsive web interfaces using the approved technology stack.
• Build and enhance conversational AI, RAG, semantic search, AI-agent, intelligent document processing, knowledge management and workflow automation capabilities.
• Integrate applications with enterprise data services, enterprise databases, vector stores, model platforms, event or messaging services, identity platforms and third party APIs.
• Implement enterprise controls for authentication and authorisation, secrets encryption, sensitive-data handling, audit logging, AI guardrails and secure software development.
• Create automated tests and AI evaluation checks; monitor quality, performance, latency, availability, safety and cost-related engineering indicators.
• Package and deploy applications through approved CI/CD pipelines, containers and Kubernetes-based environments across development, testing and production.
• Troubleshoot defects and production incidents, complete root-cause analysis and implement durable corrective actions within agreed service and delivery timelines.
• Participate in architecture and technical-design reviews, document solutions, review code and contribute to reusable engineering standards and components.
• Work closely with Product Owners, Solution Architects, Data Scientists, Cybersecurity, Data Governance, DevOps, Infrastructure, UI/UX, business teams and delivery partners; Evaluate emerging technologies where they provide measurable business value.

Skills

Python

Java

Node.js

RESTful APIs

Microservices

CI/CD

Docker

Kubernetes

Agile delivery

Git

SQL

NoSQL

Vector databases

Education

Bachelor’s Degree in Computer Science / Information Technology or equivalent

Tools

React

Vue.js

Angular

Alibaba Cloud

Azure

AWS

LLM orchestration frameworks

DevSecOps

Job description

We are looking for an experienced Senior Software Engineer to design, develop, and deliver enterprise-grade AI solutions for different Banking Domains.

You will work on a diverse range of innovative solutions including conversational AI, Retrieval-Augmented Generation (RAG) platforms, AI agents/Agentic AI, intelligent document processing, workflow automation, knowledge management systems, and enterprise integrations.

Working closely with Solution Architects, and Technical Leads. You will build scalable, secure, and production-ready applications that solve real business challenges while leveraging modern cloud and AI technologies.

Key Responsibilities

• Translate approved business use cases and solution designs into secure, scalable and maintainable enterprise applications.
• Develop backend services, microservices, RESTful APIs and, where required, responsive web interfaces using the approved technology stack.
• Build and enhance conversational AI, RAG, semantic search, AI-agent, intelligent document processing, knowledge management and workflow automation capabilities.

Integration, data and security

• Integrate applications with enterprise data services, enterprise databases, vector
• stores, model platforms, event or messaging services, identity platforms and third party APIs.
• Implement enterprise controls for authentication and authorisation, secrets encryption, sensitive-data handling, audit logging, AI guardrails and secure software development.

Engineering quality and operations

• Create automated tests and AI evaluation checks; monitor quality, performance, latency, availability, safety and cost-related engineering indicators.
• Package and deploy applications through approved CI/CD pipelines, containers and Kubernetes-based environments across development, testing and production.
• Troubleshoot defects and production incidents, complete root-cause analysis and implement durable corrective actions within agreed service and delivery timelines.

Collaboration and continuous improvement

• Participate in architecture and technical-design reviews, document solutions, review code and contribute to reusable engineering standards and components.
• Work closely with Product Owners, Solution Architects, Data Scientists, Cybersecurity, Data Governance, DevOps, Infrastructure, UI/UX, business teams and delivery partners;
• Evaluate emerging technologies where they provide measurable business value.

Qualifications

Bachelor’s Degree in Computer Science / Information Technology or equivalent.

Professional Certifications

Relevant certification in Generative AI/Agentic AI , cloud platforms (Alibaba Cloud, Azure or AWS), Kubernetes, DevSecOps, secure software development, data engineering will be an added advantage.

• Minimum 5 years of professional software engineering experience, including delivery and support of production applications.
• At least 2 years of hands-on experience with Generative AI, RAG, machine learning or intelligent automation, delivery of at least multiple production-grade AI application is highly desirable.
• Strong hands-on proficiency in Python. Experience with Java and Node.js for enterprise integration is desirable.
• Experience with modern web development using React, Vue.js or Angular.
• Strong understanding of application architecture, object-oriented programming, design patterns, clean code, RESTful APIs and microservices.
• Hands-on experience with SQL, NoSQL and vector databases, Git-based development, automated testing, Docker, Kubernetes or containerized development, CI/CD and Agile delivery.
• Practical experience with RAG pipelines, AI agents, LLM orchestration frameworks, LLM evaluation, observability, security controls and production troubleshooting is highly desirable.
• Core engineering: advanced Python, backend development, API and microservice design, clean code, automated testing and code review; Java or Node.js is beneficial.
• RAG and data: ingestion, OCR and parsing, chunking, embeddings, metadata, vector indexing, hybrid retrieval, reranking, citations and document-level access control.
• Agentic AI and LLMOps tool or MCP integration, orchestration, prompt and configuration versioning, evaluation, deployment, rollback, tracing and human-in-the-loop controls.
• Platform and reliability: cloud services, Docker, Kubernetes, CI/CD, observability, token and cost monitoring, performance optimisation, resilience and production support.
• Security and integration: OAuth2, OpenID Connect, SAML, Microsoft Entra ID, secure SDLC, sensitive-data protection, AI threat controls, event-driven architecture and enterprise API integration.
• Behavioral: ownership, analytical problem solving, attention to detail, clear communication, stakeholder collaboration, continuous learning and focus on measurable business outcomes.