Collaborate closely with engineering teams to identify bottlenecks in development workflows and provide AI-driven optimization solutions
Explore and implement technical approaches including Prompt Engineering, RAG, and AI Agents Continuously track and adopt emerging AI technologies to optimize internal platform capabilities
Bachelor's degree or above in Computer Science or a related field
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Work with cross-functional teams (such as security, IT, infra, etc) to identify and solve other issuesContinuously learn and keep up-to-date with the latest front-end technologies and best practices.
Continuously learn and keep up-to-date with the latest front-end technologies and best practices.
Participate in the development and maintenance of frontend products using diverse technologies.
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Engineer agent prompting and context management systems, including system prompt architecture, dynamic context construction, prompt versioning, and evaluation-driven prompt optimisation using automated and human evaluation frameworks.
Contribute to the design and extension of Temasek's MCP (Model Context Protocol) ecosystem by building reusable tool connectors and well-documented integrations.
4–8 years of software engineering experience with strong full-stack depth and at least 2 years focused on AI/ML system engineering — ideally building and operating agentic AI or LLM-powered products in production.
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NCS is a leading AI Tech Services company. With a 15,000-strong team across the Asia Pacific, NCS scales its platforms and capabilities to provide clients with greater agility and AI expertise across a range of Industries. Embracing a strong ecosystem of global partners, NCS transforms technology services delivery combining AI with digital resilience to drive real business impact. NCS is a subsidiary of the Singtel Group.
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Methodology adoption and best practices: Gain a deep understanding of the design methodologies utilized within the Infineon Design System. Assist project teams in adopting these methodologies and facilitate the sharing of best practices across different business lines. Actively contribute to the knowledge base by sharing insights and experiences to enhance overall efficiency and effectiveness.
Methodology improvement and advocacy: Identify methodology gaps and propose quick solutions to address them. Collaborate with methodology teams to align on long-term improvements. Demonstrate the ability to lead discussions and drive topics in the technical steering community within DES, advocating for new requirements that can enhance the overall effectiveness of the system.
Possess a bachelor's degree in electronics engineeringand with good foundation of Analog Mixed Signal support.
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Global Payment & Monetization: Implement secure, scalable micro-transaction flows to handle high-volume, low-value payments across diverse global payment gateways.
Scale the Data Layer: Manage and optimize database structures (SQL & NoSQL) to handle millions of candidate interactions and generate deep-insight reports.
Senior: 7+ years experience. You have seen systems break at scale, can architect complex features independently, and mentor others.
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Build evaluation harnesses that measure output quality, faithfulness, hallucination rate, latency, and cost across model versions and prompt changes — governing whether AI features ship or roll back.
Implement prompt engineering at the system level, including guardrails, output filtering, and red-teaming to ensure safe and reliable AI behaviour.
Integrate workflow automation platforms (e.g. n8n, Make, Power Automate) to extend AI capabilities into business operations.
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Legacy Modernization: Identify, architectural refactor, and modernize legacy codebases to systematically improve application maintainability, scalability, and information security.
Code Quality & Governance: Conduct rigorous code reviews, uphold exceptional coding standards, and provide technical guidance to junior team members.
Cross-Functional Collaboration: Partner closely with QA, Product Management, and Frontend engineering teams to validate business requirements and ensure flawless end-to-end functionality.
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AI Service Enablement: Enable enterprise-wide adoption of AI capabilities by developing reusable APIs, SDKs, templates and shared services that simplify AI integration and accelerate solution delivery across teams, while maintaining AI security and compliance within the organisation.
Agentic AI & Orchestration: Deploy and manage AI orchestration platforms and frameworks that support agentic workflows, multi-agent systems, tool integration and enterprise AI automation capabilities.
Continuous Innovation: Stay abreast of emerging developments in Generative AI, AI infrastructure, model optimisation and agentic AI technologies. Evaluate, prototype and introduce new technologies and approaches to enhance enterprise AI capabilities.
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