AI Engineer

Posted 16d ago

AI Engineer - Agensi Pekerjaan Penta Consultancy Sdn. Bhd | Career Page

Kuala Lumpur, Malaysia

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Job Openings AI Engineer

Develop, deploy and maintain AI-enabled backend services and APIs.
Build, deploy, and manage AI and data workflows using Databricks, including use of Databricks Asset Bundles for environment-aware deployments.
Integrate and consume Large Language Models (LLMs) (e.g. Gemini, Claude, GPT) for use cases such as summarization, classification, retrieval-augmented generation (RAG), and conversational AI.
Develop lightweight front-end or integration components using JavaScript to support AI-driven user experiences.
Collaborate with product, data, and platform teams to translate business requirements into scalable AI solutions.
Support model integration, API testing, logging, monitoring, and performance optimization.
Follow secure coding practices and contribute to documentation to support governance, handover, and audit readiness.

Hands-on experience with Python for backend and AI-related development.
Experience working with Databricks, including notebooks, jobs, and deployment using Databricks Asset Bundles.
Practical experience integrating and utilizing Large Language Models (LLMs) such as Gemini, Claude, or GPT via APIs.
Experience building RESTful APIs using FastAPI or similar Python frameworks.
Working knowledge of JavaScript for UI integration or service consumption.
Familiarity with cloud-based AI/data architectures and API-driven systems.
Solid understanding of machine learning and AI concepts, including model inference, prompting, embeddings, and evaluation techniques.
Experience across the AI development lifecycle, including development, testing, deployment, and monitoring.
Strong analytical, troubleshooting, and debugging skills.
Ability to write clean, maintainable, and well-documented code.
Experience working in Agile/Scrum delivery environments.
Good communication and collaboration skills, with the ability to work effectively with cross-functional teams.
Awareness of model risk, data privacy, and responsible AI practices and considerations.

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