Top Artificial Intelligence Jobs in Malaysia

Support product operations by collecting and tracking user feedback, coordinating product issues across teams, organizing requirements, analyzing basic data, maintaining web pages, and assisting with AI-related projects. The role requires cross-functional communication, problem-solving, execution skills, bilingual English and Mandarin proficiency, and availability for 3–5 days per week for at least six months.

As an AI Data Specialist, you will support AI-generated content improvement in Chinese Simplified through tasks like data collection, evaluation, and annotation.

Build, integrate, and optimize enterprise Generative AI solutions (RAG, LLMs, AI assistants). Develop APIs and backend services, manage data and vector stores, support deployment (containers, GPU inference), monitor performance, and assist senior architects with POCs and documentation.

Evaluate and annotate AI-generated multilingual and multimodal content (text, image, audio, video). Perform quality checks, identify edge cases, participate in calibration, and provide feedback to improve annotation guidelines and datasets.

Design, build, deploy, and maintain production-grade AI/ML models and services, including Generative and Agentic AI, RAG solutions, MLOps pipelines, data pipelines, observability, and compliance with security and responsible AI guidelines while collaborating with stakeholders and engineering teams.

Partner with strategic APAC customers to design, prototype, and operationalize Genesys AI-driven CX solutions. Lead discovery, architecture, integrations (CRM/ERP), POCs, KPI-driven optimization, governance, compliance, and mentor teams to drive enterprise AI adoption.

Build and operate a unified, governed AI platform (Azure, Snowflake, dbt, GitHub) enabling LLMs, RAG pipelines, agents, Copilot rollout, governance, cost control, and domain enablement across product teams.

Support development and enhancement of BI dashboards and reports, assist with data preparation, validation and modelling, collaborate with teams to translate requirements, pilot AI-enabled analytics use cases, and document BI solutions and training materials.

Support integration of classical ML and Generative AI for process applications (anomaly detection, predictive maintenance, yield optimization). Build NLP pipelines to process unstructured SMT/mechanical assembly data, automate classification/summarization/insights, develop prompt engineering strategies, document experiments, and support digital transformation and AI-driven decision support in factory processes.

Build high-performance, scalable React+TypeScript web applications for payment experiences. Design reusable UI components and optimize frontend performance while collaborating with cross-functional teams on architecture, testing, accessibility, and product delivery.

Design and deliver secure solution architectures for cloud, data, and AI initiatives. Lead product selection, conduct solution-level risk assessments, ensure compliance with governance and regulations, and collaborate with engineering, data science, and delivery teams to implement and validate secure solutions and incident response plans.

Lead country AI and automation roadmap from discovery through delivery and adoption. Design AI-enabled workflows, dashboards, document extraction and agents using Microsoft Power Platform, Copilot Studio and Azure AI. Manage stakeholders, governance, vendor selection, change management, and build internal capability to scale automation and track benefits.

Design and develop custom SAP applications using ABAP (RAP/OO), CDS Views, SAP BTP and Fiori/UI5. Embed AI capabilities (SAP AI Core, Joule, generative and predictive models) into processes, prototype AI use cases, support integration understanding, apply Agile and CI/CD, and continuously improve solution quality and maintainability.

Design and build custom SAP applications and extensions using ABAP, RAP, CDS views, SAP BTP and Fiori/UI5. Prototype and embed AI capabilities (SAP AI Core, Joule, generative AI, predictive models) into SAP processes. Ensure secure, clean-core development, evaluate emerging SAP/BTP/AI technologies, and coordinate with external partners on platform topics and SLAs.

Lead and operate enterprise Azure and Microsoft 365 platforms, manage hybrid identity (Entra ID/AD), deliver and govern AI solutions (Azure OpenAI, Azure ML, Copilot), provide L2/3 support, secure and govern cloud resources, manage on‑prem infrastructure, and drive vendor, project, and stakeholder engagement to scale AI initiatives.

Early-career full stack internship developing frontend and backend features under senior guidance. Integrate AI coding tools into workflows, translate product requirements to implementations, contribute across the product lifecycle, and suggest cross-team process improvements while learning full-stack practices.

Lead global AI-first transformation for legislative content: define strategy, prioritise AI-enabled content generation and optimisation, deploy AI-driven editorial tools, set standards, measure performance, and build editorial AI capability across regions.

Lead and align Engineering, ML, and Analytics to deliver scalable, reliable production AI and data systems. Own technical direction, architecture, MLOps, and platform reliability while partnering with Product, Sales, and Customers to ensure engineering work maps to measurable business outcomes.

Design polished mobile-first and web interfaces for BJAK's AI and financial products. Create wireframes, flows, prototypes and high-fidelity UI, maintain the design system, iterate from user feedback, and collaborate with PMs and engineers to ensure accessibility, responsiveness and pixel-perfect implementation.

The AI Data Analyst at Brooks interprets and manages data, influences AI solutions, supports development of AI models, and collaborates on strategies across teams.

Build internal AI developer productivity tools (coding assistants, retrieval systems, workflow automation). Develop LLM-powered apps for code generation, understanding, and test automation. Integrate AI across the SDLC, embed with teams to remove friction, experiment with prompt engineering, RAG, and AI agents, and evaluate emerging AI technologies.

Early-career TechOps role: build dashboards/alerts, script repetitive ticket steps, participate in RCAs, log user pain points and propose fixes, create a lightweight agent (e.g., Telegram bot) with reusable skills, optimize incident-management workflows, and write actionable runbooks to improve support-driven user experience.

Lead planning, design, delivery and promotion of a customer-service chatbot management platform. Use AI and big data to improve CS operations (corpus training, SOPs, assistant replies, summaries). Collaborate with engineering, UX, and CS teams. Monitor KPIs and user cases to drive product improvements.

Lead AI-driven growth product strategy to improve acquisition, activation, retention, cross-sell, and churn reduction. Design viral loops and referral programs, use data and user insights to inform features, manage roadmaps, run experiments, and collaborate with marketing, operations, and engineering to optimize user funnels and drive scalable organic growth.

Design, build, and deploy Python-based microservice APIs that call LLMs and generative models to automate business processes and support game services. Translate business requirements into API specs, integrate services across systems, collaborate with DevOps for cloud deployments, optimize AI model performance, write and debug core AI code, and communicate with cross-functional stakeholders.