41 AI Engineer jobs in Singapore available for remote work from home. Apply for positions such as Full Stack AI Engineer, Product Engineer - AI Investing, Product Engineer - AI Finance and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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The Full Stack AI Engineer leads the technical delivery of agentic AI programs by designing and building production-grade systems while managing client engagements. They are responsible for hands-on coding, team leadership, and establishing DevOps and AgentOps practices to ensure high-quality, scalable AI solutions.
You will own product areas within the AI Investing division, defining user problems, product scope, and success metrics. You will collaborate with engineering, design, and operations teams to launch features and iterate based on data and user feedback.
You will own product areas across financial services like insurance, payments, and investing while defining product direction and success metrics. You will collaborate with engineering, design, and operations teams to launch features and iterate based on data and user feedback.
Own product areas across financial services including insurance, payments, and savings while defining roadmaps and success metrics. Collaborate with engineering, design, and operations teams to launch features and drive iterative improvements based on data and user feedback.
You will own product areas within the AI Stockbroking division, defining user problems, roadmaps, and success metrics. You will collaborate with engineering, design, and operations teams to launch features and iterate based on data and user feedback.
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You will own the application engineering strategy and lead a team of senior engineers to build reliable, AI-powered workflows across backend and client platforms. This role involves designing robust system architectures, establishing production foundations, and partnering with ML leadership to deliver high-quality product experiences.
You will own product areas within the AI Stockbroking division, defining user problems, roadmaps, and success metrics. You will collaborate with engineering, design, and business teams to launch features and iterate based on data and user feedback.
You will own product areas within AI Finance, defining user problems, roadmaps, and success metrics while collaborating with cross-functional teams. You are responsible for launching features, monitoring performance, and iterating on products to improve user journeys and business impact.
Own product areas across financial services including insurance, payments, and investments by defining user problems and product roadmaps. Collaborate with engineering, design, and business teams to launch features, monitor performance, and drive iterative improvements.
You will own product areas across insurance, payments, and financial services, defining roadmaps and success metrics. You will collaborate with engineering, design, and business teams to turn complex financial products into simple, usable customer journeys.
You will build technical prototypes for AI verification and collaborate with external experts to translate research into practical policy tools. The role involves working across machine learning engineering, cybersecurity, and systems architecture to develop robust and auditable verification mechanisms.
You will lead the technical design and execution of complex products while remaining hands-on with coding, architecture, and production problem-solving. Additionally, you will mentor engineers, set high standards for code quality, and drive major engineering initiatives from concept to production.
Build and ship native Android features for an AI Neobank app using Kotlin and Jetpack Compose. Collaborate with product and design teams to create secure, stable, and high-performance financial service flows.
Build and ship mobile features for an AI Neobank app across Android and iOS platforms. Collaborate with product and design teams to create intuitive financial service flows and improve app performance and reliability.
Build and ship native Android features for an AI Finance Agent using Kotlin and Jetpack Compose. Focus on creating stable, secure mobile flows for financial services while optimizing app performance and user experience.
Build and ship native Android features for an AI Finance Agent using Kotlin and Jetpack Compose. Collaborate with product and design teams to optimize user journeys and improve app performance and reliability.
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Lead the transition of the card operations AI agent from internal pilot to a production-grade system. Expand agent capabilities into accounting automation and policy enablement while ensuring reliability, safety, and cost-efficiency.
Build AI-native systems, agents, and automation workflows to optimize financial services and internal operations for a Neobank app. Design and deploy reliable AI solutions focusing on accuracy, latency, and security while collaborating with product and engineering teams.
Build and maintain core backend services, APIs, and workflows for an AI Neobank app covering insurance, payments, and savings. Design reliable systems for transactions, partner integrations, and reconciliation while ensuring security and performance for regulated financial products.
Build AI-native systems, assistants, and automated workflows to optimize financial services and internal operations. Design and productionize scalable integrations between LLMs, internal data, and business systems while ensuring reliability and safety.
Build end-to-end customer-facing and internal features for an AI Neobank app, including web flows, APIs, and dashboards. Collaborate with cross-functional teams to launch financial services products and improve production reliability through analytics and feedback.
Build and ship native Android features for an AI Neobank app using Kotlin and Jetpack Compose. Focus on creating clean user flows for financial services while optimizing app performance and reliability.
Develop and implement AI solutions by designing proof-of-concepts and translating them into minimum viable products. Collaborate with cross-functional teams to optimize AI models and integrate capabilities into existing systems.
You will own the end-to-end development of AI features, from shaping model behavior to building the surrounding systems and ensuring production reliability. This involves designing agent workflows, optimizing for latency and cost, and collaborating with product teams to translate ambiguous problems into functional AI systems.
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You will own the inference and orchestration layer that powers AI interactions, ensuring high reliability and performance. This involves building production systems, designing inference pipelines, and managing monitoring and incident response.
Design and build end-to-end AI-native product features and agent workflows that handle planning, tool use, and failure recovery. Collaborate with cross-functional teams to integrate LLMs and memory systems into reliable, production-grade applications.
The role involves bridging AI research and production systems by leading research in emerging AI paradigms like autonomous agent systems, test-time compute optimization, and multimodal understanding applied to digital safety and fraud detection. Key tasks include designing multi-agent architectures, implementing state-of-the-art reasoning systems, and building advanced multimodal models for data analysis.
You will embed security by design across AI use cases, agents, and platform components while implementing controls for access, monitoring, and sandboxing. Additionally, you will drive risk remediation, manage AI-specific threats, and strengthen incident readiness through playbooks and cross-team collaboration.
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