33 AI Engineer jobs in Singapore available for remote work from home. Apply for positions such as Research Engineer - AI Verification, Lead Engineer - AI Payments App, Senior Frontend (UI) Software Engineer (AI Lab) and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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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.
You will design, build, and optimize complex UI components for a modern integration platform using advanced web technologies. You will also collaborate with product and design teams to iterate on features and resolve performance issues.
Build and ship mobile features for KIRA's AI Finance Agent across Android and iOS platforms. Collaborate with product and design teams to create intuitive flows for insurance, payments, and financial services.
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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.
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.
Lead the end-to-end architecture and development of AI-powered full-stack applications, integrating LLMs and scalable data pipelines. Provide technical leadership and mentorship to engineers while driving the technical strategy from concept to production.
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.
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Design and ship internal products, APIs, and services that enable forward-deployed teams to scale customer-facing solutions. Own the full product lifecycle from prototype to general availability within the AI GTM Platform team.
Design and maintain Go microservices to build business logic and enterprise-grade features for the Workato platform. Collaborate with Infra and SRE teams to ensure high availability, scalability, and reliability of the system.
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.
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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Design and build end-to-end full-stack applications integrating AI/ML capabilities and LLM APIs into production systems. Architect scalable backend services and data pipelines while collaborating with R&D teams to prototype user-facing solutions.
Design, build, and operationalize agentic AI solutions embedded within enterprise client environments. Lead technical discovery and integrate AI systems with enterprise platforms while ensuring production-grade governance and observability.
Debug and fix platform issues while building internal generative AI tools and copilots. Rapidly prototype proof-of-concepts for customer use cases and collaborate across teams to drive AI adoption.
The Senior AI Infrastructure Engineer will design and implement a scalable control plane and contribute to the development of high-performance storage solutions. They will collaborate with operations teams to ensure the reliability and performance of the infrastructure.
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