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GK Consulting Pte. Ltd. seeks an experienced AI/Software Engineer to bridge product vision with scalable AI delivery for enterprise clients in Singapore. You will shape architecture for next-gen AI capabilities, lead design reviews, and mentor engineers while balancing performance, security, and cost.
You will collaborate with product managers, UX, security, and cloud teams to deploy production-ready AI features, optimise prompts, and drive governance across multi-model environments.
Our Client is a fast moving International Technology Group embarking on the next phase of its AI transformation. The Group is redefining how enterprise users interact with business software by embedding intelligent capabilities that can interpret intent, coordinate tasks, and automate increasingly sophisticated workflows. To support this, they are seeking to build a Singapore onshore team of AI engineers who can bridge product vision with technical execution. This team will play a pivotal role in shaping the architecture of next-generation AI capabilities while driving delivery of production-ready solutions that will serve a global enterprise customer base.
Reporting into the Enterprise Efficiency leadership team, this team shall provide technical expertise across the design and implementation of AI-powered features that leverage modern LLMs and agent-based architectures.
Collaborate with Product Management to evaluate new concepts, determine technical viability, and translate business objectives into scalable engineering solutions.
Beyond solution delivery, establish architectural standards and help build a robust AI platform that can accelerate future product development.
Define architecture and engineering standards for intelligent application capabilities across a major enterprise product.
Develop modular AI services capable of complex planning, contextual understanding, memory management, external system integration, and orchestration across multiple AI models.
Lead technical decisions throughout the software lifecycle, from solution design and experimentation through deployment, optimisation, operational monitoring, and continuous enhancement.
Drive improvements in model quality, responsiveness, operational cost, scalability, and production reliability.
Build reusable AI components, frameworks, and internal tooling that improve engineering productivity across multiple teams.
Provide technical mentorship to engineers while promoting best practices in areas including prompt design, retrieval strategies, model evaluation, testing, and AI governance.
Work collaboratively with software engineering, infrastructure, product, UX, and security teams to deliver enterprise-grade AI capabilities that meet performance, compliance, and data protection standards.
Continuously evaluate developments across the AI landscape and identifying technologies that can strengthen the company's long-term product strategy.