Senior GenAI Engineer

Job Role:- Senior GenAI Engineer

Job Location:- Singapore

Experience:- 5+ Years

We are looking for a Senior GenAI Engineer to design, develop, and implement enterprise-grade generative AI solutions integrated with cloud platforms such as Microsoft Azure and Amazon Web Services (AWS). The role involves building scalable AI applications, integrating large language models (LLMs), developing AI agents, and collaborating with cross-functional teams to deliver high-quality GenAI solutions.

• Design, develop, and deploy GenAI solutions integrated with Azure and AWS cloud services.
• Collaborate with business and technical teams to gather requirements and define solution architecture.
• Build and maintain scalable, efficient, and secure GenAI applications.
• Integrate LLM APIs, multimodal models, and AI agents into enterprise applications.
• Optimize GenAI models and workflows for performance, accuracy, and scalability.
• Troubleshoot and resolve issues related to AI applications and cloud deployments.
• Work closely with data scientists and machine learning engineers to enhance AI capabilities.
• Provide technical guidance, code reviews, and mentoring to engineering team members.
• Stay current with advancements in GenAI, Azure AI, OpenAI, AWS, and related cloud technologies.

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
• Strong experience developing GenAI applications and integrating LLM APIs.
• Experience with Microsoft Azure services, including Azure AI Services, Azure Functions, Azure Web Apps, and related cloud services.
• Experience with AWS services such as Lambda, ECS, Fargate, DynamoDB, Bedrock, or similar cloud technologies.
• Proficiency in Python and/or Java.
• Understanding of machine learning and deep learning concepts, including model evaluation and optimization.
• Experience building AI agents and working with multimodal AI models.
• Strong problem-solving, analytical, communication, and collaboration skills.
• Ability to work effectively in a fast-paced, collaborative environment.

• Experience with Google Cloud AI services and cloud-based AI deployment.
• Knowledge of Docker, Kubernetes, and containerized application deployment.
• Familiarity with CI/CD pipelines and DevOps practices.
• Contributions to open-source AI or cloud integration projects are advantageous.