Developer jobs in Singapore

The AI Engineer with GenAI expertise is responsible for developing advanced technical solutions, integrating cutting‑edge generative AI technologies. This role requires a deep understanding of modern technical and cloud‑native practices, AI, DevOps, and machine learning technologies, particularly in generative models. You will support a wide range of customers through the "Ideation to MVP" journey, demonstrating proficiency in leading projects and ensuring delivery excellence.

• Develop solutions leveraging GenAI technologies, integrating advanced AI capabilities into cloud‑native architectures to enhance system functionality and scalability.
• Lead the design and implementation of GenAI‑driven applications, ensuring seamless integration with microservices and container‑based environments.
• Create solutions that fully leverage the capabilities of modern microservice and container‑based environments running in public, private, and hybrid clouds.
• Contribute to thought leadership across the Cloud Native domain with an expert understanding of open‑source technologies (e.g., Kubernetes/CNCF) and partner technologies.
• Collaborate on joint technical projects with partners, including Google, Microsoft, AWS, IBM, Red Hat, Intel, Cisco, and Dell/VMware.

• Engineer innovative GenAI solutions from ideation to MVP, ensuring high performance and reliability within cloud‑native frameworks.
• Optimize AI models for deployment in cloud environments, balancing efficiency and effectiveness to meet client requirements and industry standards.
• Assess existing complex solutions and recommend appropriate technical treatments to transform applications with cloud‑native/12‑factor characteristics.
• Refactor existing solutions to implement a microservices‑based architecture.

• Drive the adoption of cutting‑edge GenAI technologies within cloud‑native projects, spearheading initiatives that push the boundaries of AI integration in cloud services.
• Engage in technical innovation and support position as an industry leader.
• Author whitepapers, blogs, and speak at industry events.
• Maintain hands‑on technical credibility, stay ahead of industry trends, and mentor others.

• Provide expert guidance to clients on incorporating GenAI and machine learning into their cloud‑native systems, ensuring best practices and strategic alignment with business goals.
• Conduct workshops and briefings to educate clients on the benefits and applications of GenAI, establishing strong, trust‑based relationships.
• Perform a trusted advisor role, contributing to technical projects (PoCs and MVPs) with a strong focus on technical excellence and on‑time delivery.

• A passionate developer with 7+ years of experience in Java, Python, and Kubernetes, comfortable working as part of a paired/balanced team.
• Extensive experience in software development, with significant exposure to AI/ML technologies.
• Expertise in GenAI frameworks: Proficient in using GenAI frameworks and libraries such as LangChain, OpenAI API, and Hugging Face Transformers.
• Prompt engineering: Experience in designing and optimizing prompts for various AI models to achieve desired outputs and improve model performance.
• Strong understanding of NLP techniques and tools, including tokenization, embeddings, transformers, and language models.
• Proven experience developing complex solutions that leverage cloud‑native technologies—featuring container‑based, microservices‑based approaches; based on applying 12‑factor principles to application engineering.
• Exemplary verbal and written communication skills (English).
• Positive and solution‑oriented mindset.
• Solid experience delivering Agile and Scrum projects in a Jira‑based project management environment.
• Proven leadership skills and the ability to lead projects to ensure delivery excellence.

• Machine Learning Operations (MLOps): Experience in deploying, monitoring, and maintaining AI models in production environments using MLOps practices.
• Data engineering for AI: Skilled in data preprocessing, feature engineering, and creating pipelines to feed AI models with high‑quality data.
• AI model fine‑tuning: Proficiency in fine‑tuning pre‑trained models on specific datasets to improve performance for specialized tasks.
• AI ethics and bias mitigation: Knowledgeable about ethical considerations in AI and experienced in implementing strategies to mitigate bias in AI models.
• Knowledgeable about vector databases, LLMs, and SMLs, and integrating with such models.
• Proficient with Kubernetes and other cloud‑native technologies, including experience with commercial Kubernetes distributions (e.g., Red Hat OpenShift, VMware Tanzu, Google Anthos, Azure AKS, Amazon EKS, Google GKE).
• Deep understanding of core practices including DevOps, SRE, Agile, Scrum, Domain‑Driven Design, and familiarity with the CNCF open‑source community.
• Recognized with multiple cloud and technical certifications at a professional level, ideally including AI/ML specializations from providers like Google, Microsoft, AWS, Linux Foundation, IBM, or Red Hat.

• At least one recognized cloud professional / developer certification (AWS/Google/Microsoft).